开发笔记 第446页

#ifndef COpenniHand_H
#define COpenniHand_H

#include <XnCppWrapper.h>
#include <iostream>
#include <vector>
#include <map>

using namespace xn;
using namespace std;

class COpenniHand
{
public:
    COpenniHand();
    ~COpenniHand();

    /*OpenNI的内部初始化，属性设置*/
    bool Initial();

    /*启动OpenNI读取Kinect数据*/
    bool Start();

    /*更新OpenNI读取到的数据*/
    bool UpdateData();

    /*得到色彩图像的node*/
    ImageGenerator& getImageGenerator();

    /*得到深度图像的node*/
    DepthGenerator& getDepthGenerator();

    /*得到手势姿势的node*/
    GestureGenerator& getGestureGenerator();

    /*得到给定投影坐标的点，返回其对应真实坐标的深度值*/
    XnFloat GetProjectWorldPixpelDepth(XnPoint3D *project_world_pixpel);

    /*得到手部的node*/
    HandsGenerator& getHandGenerator();
    DepthMetaData depth_metadata_;   //返回深度图像数据
    ImageMetaData image_metadata_;   //返回彩色图像数据
    std::map<XnUserID, XnPoint3D> hand_points_;  //为了存储不同手的实时点而设置的
    std::map< XnUserID, vector<XnPoint3D> > hands_track_points_; //为了绘画后面不同手部的跟踪轨迹而设定的

private:
    /*该函数返回真代表出现了错误，返回假代表正确*/
    bool CheckError(const char* error);

    /*表示某个手势动作已经完成检测的回调函数*/
    static void XN_CALLBACK_TYPE  CBGestureRecognized(xn::GestureGenerator &generator, const XnChar *strGesture,
                                                      const XnPoint3D *pIDPosition, const XnPoint3D *pEndPosition,
                                                      void *pCookie);

    /*表示检测到某个手势开始的回调函数*/
    static void XN_CALLBACK_TYPE CBGestureProgress(xn::GestureGenerator &generator, const XnChar *strGesture,
                                                   const XnPoint3D *pPosition, XnFloat fProgress, void *pCookie);

    /*手部开始建立的回调函数*/
    static void XN_CALLBACK_TYPE HandCreate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition,
                                            XnFloat fTime, void* pCookie);

    /*手部开始更新的回调函数*/
    static void XN_CALLBACK_TYPE HandUpdate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition, XnFloat fTime,
                                            void* pCookie);

    /*手部销毁的回调函数*/
    static void XN_CALLBACK_TYPE HandDestroy(HandsGenerator& rHands, XnUserID xUID, XnFloat fTime, void* pCookie);

    XnStatus status_;
    Context context_;
    XnMapOutputMode xmode_;
    ImageGenerator  image_generator_;
    DepthGenerator  depth_generator_;
    GestureGenerator gesture_generator_;
    HandsGenerator  hand_generator_;
};

#endif // COpenniHand_H

#include "copennihand.h"
#include <XnCppWrapper.h>
#include <iostream>
#include <map>

using namespace xn;
using namespace std;

COpenniHand::COpenniHand()
{
}

COpenniHand::~COpenniHand()
{
}

bool COpenniHand::Initial()
{
    status_ = context_.Init();
    if(CheckError("Context initial failed!")) {
        return false;
    }

    context_.SetGlobalMirror(true);//设置镜像
    xmode_.nXRes = 640;
    xmode_.nYRes = 480;
    xmode_.nFPS = 30;

    //产生颜色node
    status_ = image_generator_.Create(context_);
    if(CheckError("Create image generator  error!")) {
        return false;
    }

    //设置颜色图片输出模式
    status_ = image_generator_.SetMapOutputMode(xmode_);
    if(CheckError("SetMapOutputMdoe error!")) {
        return false;
    }

    //产生深度node
    status_ = depth_generator_.Create(context_);
    if(CheckError("Create depth generator  error!")) {
        return false;
    }

    //设置深度图片输出模式
    status_ = depth_generator_.SetMapOutputMode(xmode_);
    if(CheckError("SetMapOutputMdoe error!")) {
        return false;
    }

    //产生手势node
    status_ = gesture_generator_.Create(context_);
    if(CheckError("Create gesture generator error!")) {
        return false;
    }

    /*添加手势识别的种类*/
    gesture_generator_.AddGesture("Wave", NULL);
    gesture_generator_.AddGesture("click", NULL);
    gesture_generator_.AddGesture("RaiseHand", NULL);
    gesture_generator_.AddGesture("MovingHand", NULL);

    //产生手部的node
    status_ = hand_generator_.Create(context_);
    if(CheckError("Create hand generaotr error!")) {
        return false;
    }

    //视角校正
    status_ = depth_generator_.GetAlternativeViewPointCap().SetViewPoint(image_generator_);
    if(CheckError("Can't set the alternative view point on depth generator!")) {
        return false;
    }

    //设置与手势有关的回调函数
    XnCallbackHandle gesture_cb;
    gesture_generator_.RegisterGestureCallbacks(CBGestureRecognized, CBGestureProgress, this, gesture_cb);

    //设置于手部有关的回调函数
    XnCallbackHandle hands_cb;
    hand_generator_.RegisterHandCallbacks(HandCreate, HandUpdate, HandDestroy, this, hands_cb);

    return true;
}

bool COpenniHand::Start()
{
    status_ = context_.StartGeneratingAll();
    if(CheckError("Start generating error!")) {
        return false;
    }
    return true;
}

bool COpenniHand::UpdateData()
{
    status_ = context_.WaitNoneUpdateAll();
    if(CheckError("Update date error!")) {
        return false;
    }
    //获取数据
    image_generator_.GetMetaData(image_metadata_);
    depth_generator_.GetMetaData(depth_metadata_);

    return true;
}

ImageGenerator &COpenniHand::getImageGenerator()
{
    return image_generator_;
}

DepthGenerator &COpenniHand::getDepthGenerator()
{
    return depth_generator_;
}

GestureGenerator &COpenniHand::getGestureGenerator()
{
    return gesture_generator_;
}

HandsGenerator &COpenniHand::getHandGenerator()
{
    return hand_generator_;
}

bool COpenniHand::CheckError(const char *error)
{
    if(status_ != XN_STATUS_OK) {
        cerr << error << ": " << xnGetStatusString( status_ ) << endl;
        return true;
    }
    return false;
}

void COpenniHand::CBGestureRecognized(GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pIDPosition, const XnPoint3D *pEndPosition, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    openni->hand_generator_.StartTracking(*pEndPosition);
}

void COpenniHand::CBGestureProgress(GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pPosition, XnFloat fProgress, void *pCookie)
{
}

void COpenniHand::HandCreate(HandsGenerator &rHands, XnUserID xUID, const XnPoint3D *pPosition, XnFloat fTime, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    XnPoint3D project_pos;
    openni->depth_generator_.ConvertRealWorldToProjective(1, pPosition, &project_pos);
    pair<XnUserID, XnPoint3D> hand_point_pair(xUID, XnPoint3D());//在进行pair类型的定义时，可以将第2个设置为空
    hand_point_pair.second = project_pos;
    openni->hand_points_.insert(hand_point_pair);//将检测到的手部存入map类型的hand_points_中。

    pair<XnUserID, vector<XnPoint3D>> hand_track_point(xUID, vector<XnPoint3D>());
    hand_track_point.second.push_back(project_pos);
    openni->hands_track_points_.insert(hand_track_point);
}

void COpenniHand::HandUpdate(HandsGenerator &rHands, XnUserID xUID, const XnPoint3D *pPosition, XnFloat fTime, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    XnPoint3D project_pos;
    openni->depth_generator_.ConvertRealWorldToProjective(1, pPosition, &project_pos);
    openni->hand_points_.find(xUID)->second = project_pos;
    openni->hands_track_points_.find(xUID)->second.push_back(project_pos);
}

void COpenniHand::HandDestroy(HandsGenerator &rHands, XnUserID xUID, XnFloat fTime, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    openni->hand_points_.erase(openni->hand_points_.find(xUID));
    openni->hands_track_points_.erase(openni->hands_track_points_.find(xUID ));
}

#ifndef CKINECTOPENCV_H
#define CKINECTOPENCV_H

#include <opencv2/core/core.hpp>
#include "copennihand.h"
#include "XnCppWrapper.h"

using namespace cv;
using namespace xn;

class CKinectOpenCV
{
public:
    CKinectOpenCV();
    ~CKinectOpenCV();
    void GetAllInformation();   //在返回有用信息前调用该函数，因为openni的数据在不断更新，信息的处理最好放在一个函数中
    Mat GetColorImage() ;
    Mat GetDepthImage() ;
    Mat GetDepthRealValueImage();
    std::map<XnUserID, XnPoint3D> GetHandPoints();

private:
    COpenniHand openni_hand_;
    std::map<XnUserID, XnPoint3D> hand_points_;  //为了存储不同手的实时点而设置的
    Mat color_image_;    //颜色图像
    Mat depth_image_;    //深度图像
    Mat depth_realvalue_image_;

};

#endif // CKINECTOPENCV_H

#include "ckinectopencv.h"
#include <opencv2/imgproc/imgproc.hpp>
#include <map>

using namespace cv;
using namespace std;

#define DEPTH_SCALE_FACTOR 255./4096.

CKinectOpenCV::CKinectOpenCV()
{   
    /*初始化openni对应的设备*/
     CV_Assert(openni_hand_.Initial());

    /*启动openni对应的设备*/
    CV_Assert(openni_hand_.Start());
}

CKinectOpenCV::~CKinectOpenCV()
{
}

void CKinectOpenCV::GetAllInformation()
{
    CV_Assert(openni_hand_.UpdateData());
    /*获取色彩图像*/
    Mat color_image_src(openni_hand_.image_metadata_.YRes(), openni_hand_.image_metadata_.XRes(),
                        CV_8UC3, (char *)openni_hand_.image_metadata_.Data());
    cvtColor(color_image_src, color_image_, CV_RGB2BGR);

    /*获取深度图像*/
    Mat depth_image_src(openni_hand_.depth_metadata_.YRes(), openni_hand_.depth_metadata_.XRes(),
                        CV_16UC1, (char *)openni_hand_.depth_metadata_.Data());//因为kinect获取到的深度图像实际上是无符号的16位数据
    depth_image_src.convertTo(depth_image_, CV_8U, DEPTH_SCALE_FACTOR);

    /*获取真实深度值图像，没有经过深度归一化的*/
    depth_realvalue_image_ = depth_image_src.clone();

    hand_points_ = openni_hand_.hand_points_;   //返回手部点的位置

    return;
}

Mat CKinectOpenCV::GetColorImage()
{
    return color_image_;
}

Mat CKinectOpenCV::GetDepthImage()
{
    return depth_image_;
}

Mat CKinectOpenCV::GetDepthRealValueImage()
{
    return depth_realvalue_image_;
}

std::map<XnUserID, XnPoint3D> CKinectOpenCV::GetHandPoints()
{
    return hand_points_;
}

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include "ckinectopencv.h"
#include "XnCppWrapper.h"

using namespace std;
using namespace cv;

CKinectOpenCV kinect_opencv;
Mat color_image ;
Mat depth_image ;
Mat depth_realvalue_image;
unsigned int  pixpel_depth_value = 0;

Point mouse_pixpel(0, 0);

void on_mouse(int event,int x,int y,int,void*)
{
    if(event == CV_EVENT_MOUSEMOVE) {  //鼠标移动的过程中
        pixpel_depth_value = depth_realvalue_image.at<unsigned short int>(y, x);
        mouse_pixpel = Point(x, y);
    }
}

int main()
{

//    namedWindow("color_image", CV_WINDOW_AUTOSIZE);
    namedWindow("depth_image", CV_WINDOW_AUTOSIZE);
    setMouseCallback("depth_image", on_mouse, 0);   //设置鼠标响应函数

    while(1)
    {
        kinect_opencv.GetAllInformation();
//        color_image = kinect_opencv.GetColorImage();
        depth_image = kinect_opencv.GetDepthImage();
        depth_realvalue_image = kinect_opencv.GetDepthRealValueImage();
        stringstream depth_value_string;
        depth_value_string << pixpel_depth_value/1000. << " m" ;

        putText(depth_image, depth_value_string.str(), mouse_pixpel, 3, 1, Scalar(50, 0, 0), 2, 8);

//        imshow("color_image", color_image);
        imshow("depth_image", depth_image);
        waitKey(30);
    }

    return 0;
}

#ifndef COpenniHand_H
#define COpenniHand_H

#include <XnCppWrapper.h>
#include <iostream>
#include <vector>
#include <map>

using namespace xn;
using namespace std;

class COpenniHand
{
public:
    COpenniHand();
    ~COpenniHand();

    /*OpenNI的内部初始化，属性设置*/
    bool Initial();

    /*启动OpenNI读取Kinect数据*/
    bool Start();

    /*更新OpenNI读取到的数据*/
    bool UpdateData();

    /*得到色彩图像的node*/
    ImageGenerator& getImageGenerator();

    /*得到深度图像的node*/
    DepthGenerator& getDepthGenerator();

    /*得到手势姿势的node*/
    GestureGenerator& getGestureGenerator();

    /*得到手部的node*/
    HandsGenerator& getHandGenerator();
    DepthMetaData depth_metadata_;   //返回深度图像数据
    ImageMetaData image_metadata_;   //返回彩色图像数据
    std::map<XnUserID, XnPoint3D> hand_points_;  //为了存储不同手的实时点而设置的
    std::map< XnUserID, vector<XnPoint3D> > hands_track_points_; //为了绘画后面不同手部的跟踪轨迹而设定的

private:
    /*该函数返回真代表出现了错误，返回假代表正确*/
    bool CheckError(const char* error);

    /*表示某个手势动作已经完成检测的回调函数*/
    static void XN_CALLBACK_TYPE  CBGestureRecognized(xn::GestureGenerator &generator, const XnChar *strGesture,
                                                      const XnPoint3D *pIDPosition, const XnPoint3D *pEndPosition,
                                                      void *pCookie);

    /*表示检测到某个手势开始的回调函数*/
    static void XN_CALLBACK_TYPE CBGestureProgress(xn::GestureGenerator &generator, const XnChar *strGesture,
                                                   const XnPoint3D *pPosition, XnFloat fProgress, void *pCookie);

    /*手部开始建立的回调函数*/
    static void XN_CALLBACK_TYPE HandCreate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition,
                                            XnFloat fTime, void* pCookie);

    /*手部开始更新的回调函数*/
    static void XN_CALLBACK_TYPE HandUpdate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition, XnFloat fTime,
                                            void* pCookie);

    /*手部销毁的回调函数*/
    static void XN_CALLBACK_TYPE HandDestroy(HandsGenerator& rHands, XnUserID xUID, XnFloat fTime, void* pCookie);

    XnStatus status_;
    Context context_;
    XnMapOutputMode xmode_;
    ImageGenerator  image_generator_;
    DepthGenerator  depth_generator_;
    GestureGenerator gesture_generator_;
    HandsGenerator  hand_generator_;
};

#endif // COpenniHand_H

#include "copennihand.h"
#include <XnCppWrapper.h>
#include <iostream>
#include <map>

using namespace xn;
using namespace std;

COpenniHand::COpenniHand()
{
}

COpenniHand::~COpenniHand()
{
}

bool COpenniHand::Initial()
{
    status_ = context_.Init();
    if(CheckError("Context initial failed!")) {
        return false;
    }

    context_.SetGlobalMirror(true);//设置镜像
    xmode_.nXRes = 640;
    xmode_.nYRes = 480;
    xmode_.nFPS = 30;

    //产生颜色node
    status_ = image_generator_.Create(context_);
    if(CheckError("Create image generator  error!")) {
        return false;
    }

    //设置颜色图片输出模式
    status_ = image_generator_.SetMapOutputMode(xmode_);
    if(CheckError("SetMapOutputMdoe error!")) {
        return false;
    }

    //产生深度node
    status_ = depth_generator_.Create(context_);
    if(CheckError("Create depth generator  error!")) {
        return false;
    }

    //设置深度图片输出模式
    status_ = depth_generator_.SetMapOutputMode(xmode_);
    if(CheckError("SetMapOutputMdoe error!")) {
        return false;
    }

    //产生手势node
    status_ = gesture_generator_.Create(context_);
    if(CheckError("Create gesture generator error!")) {
        return false;
    }

    /*添加手势识别的种类*/
    gesture_generator_.AddGesture("Wave", NULL);
    gesture_generator_.AddGesture("click", NULL);
    gesture_generator_.AddGesture("RaiseHand", NULL);
    gesture_generator_.AddGesture("MovingHand", NULL);

    //产生手部的node
    status_ = hand_generator_.Create(context_);
    if(CheckError("Create hand generaotr error!")) {
        return false;
    }

    //视角校正
    status_ = depth_generator_.GetAlternativeViewPointCap().SetViewPoint(image_generator_);
    if(CheckError("Can't set the alternative view point on depth generator!")) {
        return false;
    }

    //设置与手势有关的回调函数
    XnCallbackHandle gesture_cb;
    gesture_generator_.RegisterGestureCallbacks(CBGestureRecognized, CBGestureProgress, this, gesture_cb);

    //设置于手部有关的回调函数
    XnCallbackHandle hands_cb;
    hand_generator_.RegisterHandCallbacks(HandCreate, HandUpdate, HandDestroy, this, hands_cb);

    return true;
}

bool COpenniHand::Start()
{
    status_ = context_.StartGeneratingAll();
    if(CheckError("Start generating error!")) {
        return false;
    }
    return true;
}

bool COpenniHand::UpdateData()
{
    status_ = context_.WaitNoneUpdateAll();
    if(CheckError("Update date error!")) {
        return false;
    }
    //获取数据
    image_generator_.GetMetaData(image_metadata_);
    depth_generator_.GetMetaData(depth_metadata_);

    return true;
}

ImageGenerator &COpenniHand::getImageGenerator()
{
    return image_generator_;
}

DepthGenerator &COpenniHand::getDepthGenerator()
{
    return depth_generator_;
}

GestureGenerator &COpenniHand::getGestureGenerator()
{
    return gesture_generator_;
}

HandsGenerator &COpenniHand::getHandGenerator()
{
    return hand_generator_;
}

bool COpenniHand::CheckError(const char *error)
{
    if(status_ != XN_STATUS_OK) {
        cerr << error << ": " << xnGetStatusString( status_ ) << endl;
        return true;
    }
    return false;
}

void COpenniHand::CBGestureRecognized(GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pIDPosition, const XnPoint3D *pEndPosition, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    openni->hand_generator_.StartTracking(*pEndPosition);
}

void COpenniHand::CBGestureProgress(GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pPosition, XnFloat fProgress, void *pCookie)
{
}

void COpenniHand::HandCreate(HandsGenerator &rHands, XnUserID xUID, const XnPoint3D *pPosition, XnFloat fTime, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    XnPoint3D project_pos;
    openni->depth_generator_.ConvertRealWorldToProjective(1, pPosition, &project_pos);
    pair<XnUserID, XnPoint3D> hand_point_pair(xUID, XnPoint3D());//在进行pair类型的定义时，可以将第2个设置为空
    hand_point_pair.second = project_pos;
    openni->hand_points_.insert(hand_point_pair);//将检测到的手部存入map类型的hand_points_中。

    pair<XnUserID, vector<XnPoint3D>> hand_track_point(xUID, vector<XnPoint3D>());
    hand_track_point.second.push_back(project_pos);
    openni->hands_track_points_.insert(hand_track_point);
}

void COpenniHand::HandUpdate(HandsGenerator &rHands, XnUserID xUID, const XnPoint3D *pPosition, XnFloat fTime, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    XnPoint3D project_pos;
    openni->depth_generator_.ConvertRealWorldToProjective(1, pPosition, &project_pos);
    openni->hand_points_.find(xUID)->second = project_pos;
    openni->hands_track_points_.find(xUID)->second.push_back(project_pos);
}

void COpenniHand::HandDestroy(HandsGenerator &rHands, XnUserID xUID, XnFloat fTime, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    openni->hand_points_.erase(openni->hand_points_.find(xUID));
    openni->hands_track_points_.erase(openni->hands_track_points_.find(xUID ));
}

#ifndef CKINECTOPENCV_H
#define CKINECTOPENCV_H

#include <opencv2/core/core.hpp>
#include "copennihand.h"

using namespace cv;

class CKinectOpenCV
{
public:
    CKinectOpenCV();
    ~CKinectOpenCV();
    void GetAllInformation();   //在返回有用信息前调用该函数，因为openni的数据在不断更新，信息的处理最好放在一个函数中
    Mat GetColorImage() ;
    Mat GetDepthImage() ;
    std::map<XnUserID, XnPoint3D> GetHandPoints();

private:
    COpenniHand openni_hand_;
    std::map<XnUserID, XnPoint3D> hand_points_;  //为了存储不同手的实时点而设置的
    Mat color_image_;    //颜色图像
    Mat depth_image_;    //深度图像


};

#endif // CKINECTOPENCV_H

#include "ckinectopencv.h"
#include <opencv2/imgproc/imgproc.hpp>
#include <map>

using namespace cv;
using namespace std;

#define DEPTH_SCALE_FACTOR 255./4096.

CKinectOpenCV::CKinectOpenCV()
{   
    /*初始化openni对应的设备*/
     CV_Assert(openni_hand_.Initial());

    /*启动openni对应的设备*/
    CV_Assert(openni_hand_.Start());
}

CKinectOpenCV::~CKinectOpenCV()
{
}

void CKinectOpenCV::GetAllInformation()
{
    CV_Assert(openni_hand_.UpdateData());
    /*获取色彩图像*/
    Mat color_image_src(openni_hand_.image_metadata_.YRes(), openni_hand_.image_metadata_.XRes(),
                        CV_8UC3, (char *)openni_hand_.image_metadata_.Data());
    cvtColor(color_image_src, color_image_, CV_RGB2BGR);

    /*获取深度图像*/
    Mat depth_image_src(openni_hand_.depth_metadata_.YRes(), openni_hand_.depth_metadata_.XRes(),
                        CV_16UC1, (char *)openni_hand_.depth_metadata_.Data());//因为kinect获取到的深度图像实际上是无符号的16位数据
    depth_image_src.convertTo(depth_image_, CV_8U, DEPTH_SCALE_FACTOR);

    hand_points_ = openni_hand_.hand_points_;   //返回手部点的位置

    return;
}

Mat CKinectOpenCV::GetColorImage()
{
    return color_image_;
}

Mat CKinectOpenCV::GetDepthImage()
{
    return depth_image_;
}

std::map<XnUserID, XnPoint3D> CKinectOpenCV::GetHandPoints()
{
    return hand_points_;
}

#ifndef KINECTHAND_H
#define KINECTHAND_H

#include "ckinectopencv.h"

using namespace cv;

#define MAX_HANDS_COLOR 10
#define MAX_HANDS_NUMBER  10

class CKinectHandSegment
{
public:
    CKinectHandSegment();
    ~CKinectHandSegment();
    void Initial();
    void StartKinectHand(); //启动kinect手部设备驱动
    Mat GetColorImageWithHandsPoint();
    Mat GetHandSegmentImage();
    Mat GetHandHandlingImage();
    Mat GetColorImage();
    Mat GetDepthImage();

private:
    CKinectOpenCV kinect_opencv_;
    vector<Scalar> hand_center_color_array_;//采用默认的10种颜色
    std::map<XnUserID, XnPoint3D> hand_points_;
    vector<unsigned int> hand_depth_;
    vector<Rect> hands_roi_;
    bool hand_segment_flag_;
    Mat color_image_with_handspoint_;   //带有手部中心位置的色彩图
    Mat color_image_;   //色彩图
    Mat depth_image_;
    Mat hand_segment_image_;
    Mat hand_handling_image_;
    Mat hand_segment_mask_;
};

#endif // KINECTHAND_H

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include "ckinecthandsegment.h"
#include "copennihand.h"
#include "ckinectopencv.h"

using namespace cv;
using namespace std;

#define DEPTH_SCALE_FACTOR 255./4096.
#define ROI_HAND_WIDTH 140
#define ROI_HAND_HEIGHT 140
#define MEDIAN_BLUR_K 5
#define XRES  640
#define YRES  480
#define DEPTH_SEGMENT_THRESH 5
#define HAND_LIKELY_AREA 2000

CKinectHandSegment::CKinectHandSegment()
{
}

CKinectHandSegment::~CKinectHandSegment()
{
}

void CKinectHandSegment::Initial()
{
    color_image_with_handspoint_ = kinect_opencv_.GetColorImage();
    depth_image_ = kinect_opencv_.GetDepthImage();
    {
        hand_center_color_array_.push_back(Scalar(255, 0, 0));
        hand_center_color_array_.push_back(Scalar(0, 255, 0));
        hand_center_color_array_.push_back(Scalar(0, 0, 255));
        hand_center_color_array_.push_back(Scalar(255, 0, 255));
        hand_center_color_array_.push_back(Scalar(255, 255, 0));
        hand_center_color_array_.push_back(Scalar(0, 255, 255));
        hand_center_color_array_.push_back(Scalar(128, 255, 0));
        hand_center_color_array_.push_back(Scalar(0, 128, 255));
        hand_center_color_array_.push_back(Scalar(255, 0, 128));
        hand_center_color_array_.push_back(Scalar(255, 128, 255));
    }
    vector<unsigned int> hand_depth_temp(MAX_HANDS_NUMBER, 0);
    hand_depth_ = hand_depth_temp;
    vector<Rect> hands_roi_temp(MAX_HANDS_NUMBER, Rect(XRES/2, YRES/2, ROI_HAND_WIDTH, ROI_HAND_HEIGHT));
    hands_roi_ = hands_roi_temp;
}

void CKinectHandSegment::StartKinectHand()
{
    kinect_opencv_.GetAllInformation();
}

Mat CKinectHandSegment::GetColorImage()
{
    return kinect_opencv_.GetColorImage();
}

Mat CKinectHandSegment::GetDepthImage()
{
    return kinect_opencv_.GetDepthImage();
}

/*该函数只是在Kinect获取的色彩图片上将手的中心点位置画出来而已，图片的其它地方不变*/
Mat CKinectHandSegment::GetColorImageWithHandsPoint()
{
    color_image_with_handspoint_ = kinect_opencv_.GetColorImage();
    hand_points_ = kinect_opencv_.GetHandPoints();
    for(auto itUser = hand_points_.cbegin(); itUser != hand_points_.cend(); ++itUser) {
        circle(color_image_with_handspoint_, Point(itUser->second.X, itUser->second.Y),
               5, hand_center_color_array_.at(itUser->first % hand_center_color_array_.size()), 3, 8);
    }

    return color_image_with_handspoint_;
}

Mat CKinectHandSegment::GetHandSegmentImage()
{
    hand_segment_flag_ = false;
    color_image_ = kinect_opencv_.GetColorImage();
    depth_image_ = kinect_opencv_.GetDepthImage();
    hand_points_ = kinect_opencv_.GetHandPoints();
    hand_segment_mask_ = Mat::zeros(color_image_.size(), CV_8UC1);  //  因为zeros是一个静态函数，所以不能直接用具体的对象去调用，而需要用类来调用

    for(auto itUser = hand_points_.cbegin(); itUser != hand_points_.cend(); ++itUser) {

        /*设置不同手部的深度*/
        hand_depth_.at(itUser->first % MAX_HANDS_COLOR) = (unsigned int)(itUser->second.Z* DEPTH_SCALE_FACTOR);//itUser->first会导致程序出现bug

        /*设置不同手部的不同感兴趣区域*/
        hands_roi_.at(itUser->first % MAX_HANDS_NUMBER) = Rect(itUser->second.X - ROI_HAND_WIDTH/2, itUser->second.Y - ROI_HAND_HEIGHT/2,
                                           ROI_HAND_WIDTH, ROI_HAND_HEIGHT);
        hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x =  itUser->second.X - ROI_HAND_WIDTH/2;
        hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y =  itUser->second.Y - ROI_HAND_HEIGHT/2;
        hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).width = ROI_HAND_WIDTH;
        hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).height = ROI_HAND_HEIGHT;
        if(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x <= 0)
            hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x  = 0;
        if(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x > XRES)
            hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x =  XRES;
        if(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y <= 0)
            hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y = 0;
        if(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y > YRES)
            hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y =  YRES;
    }

    //取出手的mask部分,不管原图像时多少通道的，mask矩阵声明为单通道就ok
    for(auto itUser = hand_points_.cbegin(); itUser != hand_points_.cend(); ++itUser) {
        for(int i = hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x; i < min(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x+hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).width, XRES); i++)
            for(int j = hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y; j < min(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y+hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).height, YRES); j++) {
                hand_segment_mask_.at<unsigned char>(j, i) = ((hand_depth_.at(itUser->first % MAX_HANDS_NUMBER)-DEPTH_SEGMENT_THRESH) < depth_image_.at<unsigned char>(j, i))
                                                            & ((hand_depth_.at(itUser->first % MAX_HANDS_NUMBER)+DEPTH_SEGMENT_THRESH) > depth_image_.at<unsigned char>(j,i));
                hand_segment_mask_.at<unsigned char>(j, i) = 255*hand_segment_mask_.at<unsigned char>(j, i);
            }
        }

    medianBlur(hand_segment_mask_, hand_segment_mask_, MEDIAN_BLUR_K);
    hand_segment_image_.convertTo(hand_segment_image_, CV_8UC3, 0, 0 ); //  需要清零
    color_image_.copyTo(hand_segment_image_, hand_segment_mask_);
    hand_segment_flag_ = true;  //返回之前将分割标志置位为1，表示已经完成分割函数

    return hand_segment_image_;
}

Mat CKinectHandSegment::GetHandHandlingImage()
{
    /*对mask图像进行轮廓提取,并在手势识别图像中画出来*/
    std::vector< std::vector<Point> > contours;
    CV_Assert(hand_segment_flag_);  //  因为后面要用到分割函数的mask图，所以这里先要保证调用过分割函数
    findContours(hand_segment_mask_, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);//找出mask图像的轮廓
    hand_handling_image_ = Mat::zeros(color_image_.rows, color_image_.cols, CV_8UC3);

    for(int i = 0; i < contours.size(); i++) {  //只有在检测到轮廓时才会去求它的多边形，凸包集，凹陷集
        /*找出轮廓图像多边形拟合曲线*/
        Mat contour_mat = Mat(contours[i]);
        if(contourArea(contour_mat) > HAND_LIKELY_AREA) {   //比较有可能像手的区域
            std::vector<Point> approx_poly_curve;
            approxPolyDP(contour_mat, approx_poly_curve, 10, true);//找出轮廓的多边形拟合曲线
            std::vector< std::vector<Point> > approx_poly_curve_debug;
            approx_poly_curve_debug.push_back(approx_poly_curve);

             drawContours(hand_handling_image_, contours, i, Scalar(255, 0, 0), 1, 8); //画出轮廓
//            drawContours(hand_handling_image_, approx_poly_curve_debug, 0, Scalar(256, 128, 128), 1, 8); //画出多边形拟合曲线

            /*对求出的多边形拟合曲线求出其凸包集*/
            vector<int> hull;
            convexHull(Mat(approx_poly_curve), hull, true);
            for(int i = 0; i < hull.size(); i++) {
                circle(hand_handling_image_, approx_poly_curve[hull[i]], 2, Scalar(0, 255, 0), 2, 8);
            }

            /*对求出的多边形拟合曲线求出凹陷集*/
            std::vector<Vec4i> convexity_defects;
            if(Mat(approx_poly_curve).checkVector(2, CV_32S) > 3)
                convexityDefects(approx_poly_curve, Mat(hull), convexity_defects);
            for(int i = 0; i < convexity_defects.size(); i++) {
                circle(hand_handling_image_, approx_poly_curve[convexity_defects[i][2]] , 2, Scalar(0, 0, 255), 2, 8);

            }
        }
    }

    /**画出手势的中心点**/
    for(auto itUser = hand_points_.cbegin(); itUser != hand_points_.cend(); ++itUser) {
        circle(hand_handling_image_, Point(itUser->second.X, itUser->second.Y), 3, Scalar(0, 255, 255), 3, 8);
    }

    return hand_handling_image_;
}

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include "ckinectopencv.h"
#include "ckinecthandsegment.h"

using namespace std;
using namespace cv;

int main()
{
    CKinectHandSegment kinect_hand_segment;
    Mat color_image ;
    Mat depth_image ;
    Mat hand_segment;
    Mat hand_handling_image;

    kinect_hand_segment.Initial();
    while(1)
    {
        kinect_hand_segment.StartKinectHand();
        color_image = kinect_hand_segment.GetColorImageWithHandsPoint();
        hand_segment = kinect_hand_segment.GetHandSegmentImage();
        hand_handling_image = kinect_hand_segment.GetHandHandlingImage();
        depth_image = kinect_hand_segment.GetDepthImage();

        imshow("color_image", color_image);
        imshow("depth_image", depth_image);
        imshow("hand_segment", hand_segment);
        imshow("hand_handling", hand_handling_image);
        waitKey(30);
    }

    return 0;
}

int Mat::checkVector(int _elemChannels, int _depth, bool _requireContinuous) const

{

    return (depth() == _depth || _depth <= 0) &&

        (isContinuous() || !_requireContinuous) &&

        ((dims == 2 && (((rows == 1 || cols == 1) && channels() == _elemChannels) || (cols == _elemChannels))) ||

        (dims == 3 && channels() == 1 && size.p[2] == _elemChannels && (size.p[0] == 1 || size.p[1] == 1) &&

         (isContinuous() || step.p[1] == step.p[2]*size.p[2])))

    ? (int)(total()*channels()/_elemChannels) : -1;

}

struct CvConvexityDefect

{

   CvPoint* start; // point of the contour where the defect begins

   CvPoint* end; // point of the contour where the defect ends

   CvPoint* depth_point; // the farthest from the convex hull point within the defect

   float depth; // distance between the farthest point and the convex hull

};

#include <iostream>

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <opencv2/core/core.hpp>
#include "copenni.cpp"

#include <iostream>

#define DEPTH_SCALE_FACTOR 255./4096.
#define ROI_HAND_WIDTH 140
#define ROI_HAND_HEIGHT 140
#define MEDIAN_BLUR_K 5
#define XRES  640
#define YRES  480
#define DEPTH_SEGMENT_THRESH 5
#define MAX_HANDS_COLOR 10
#define MAX_HANDS_NUMBER  10
#define HAND_LIKELY_AREA 2000
#define DELTA_POINT_DISTENCE 25     //手部中心点1和中心点2距离的阈值
#define SEGMENT_POINT1_DISTANCE 27  //凸点与手部中心点1远近距离的阈值
#define SEGMENT_POINT2_DISTANCE 30  //凸点与手部中心点2远近距离的阈值

using namespace cv;
using namespace xn;
using namespace std;

int main (int argc, char **argv)
{
    unsigned int convex_number_above_point1 = 0;
    unsigned int concave_number_above_point1 = 0;
    unsigned int convex_number_above_point2 = 0;
    unsigned int concave_number_above_point2 = 0;
    unsigned int convex_assist_above_point1 = 0;
    unsigned int convex_assist_above_point2 = 0;
    unsigned int point_y1 = 0;
    unsigned int point_y2 = 0;
    int number_result = -1;
    bool recognition_flag = false;  //开始手部数字识别的标志

    vector<Scalar> color_array;//采用默认的10种颜色
    {
        color_array.push_back(Scalar(255, 0, 0));
        color_array.push_back(Scalar(0, 255, 0));
        color_array.push_back(Scalar(0, 0, 255));
        color_array.push_back(Scalar(255, 0, 255));
        color_array.push_back(Scalar(255, 255, 0));
        color_array.push_back(Scalar(0, 255, 255));
        color_array.push_back(Scalar(128, 255, 0));
        color_array.push_back(Scalar(0, 128, 255));
        color_array.push_back(Scalar(255, 0, 128));
        color_array.push_back(Scalar(255, 128, 255));
    }
    vector<unsigned int> hand_depth(MAX_HANDS_NUMBER, 0);
    vector<Rect> hands_roi(MAX_HANDS_NUMBER, Rect(XRES/2, YRES/2, ROI_HAND_WIDTH, ROI_HAND_HEIGHT));

    namedWindow("color image", CV_WINDOW_AUTOSIZE);
    namedWindow("depth image", CV_WINDOW_AUTOSIZE);
    namedWindow("hand_segment", CV_WINDOW_AUTOSIZE);    //显示分割出来的手的区域
    namedWindow("handrecognition", CV_WINDOW_AUTOSIZE); //显示0~5数字识别的图像

    COpenNI openni;
    if(!openni.Initial())
        return 1;

    if(!openni.Start())
        return 1;
    while(1) {
        if(!openni.UpdateData()) {
            return 1;
        }
        /*获取并显示色彩图像*/
        Mat color_image_src(openni.image_metadata_.YRes(), openni.image_metadata_.XRes(),
                            CV_8UC3, (char *)openni.image_metadata_.Data());
        Mat color_image;
        cvtColor(color_image_src, color_image, CV_RGB2BGR);
        Mat hand_segment_mask(color_image.size(), CV_8UC1, Scalar::all(0));

        for(auto itUser = openni.hand_points_.cbegin(); itUser != openni.hand_points_.cend(); ++itUser) {

            point_y1 = itUser->second.Y;
            point_y2 = itUser->second.Y + DELTA_POINT_DISTENCE;
            circle(color_image, Point(itUser->second.X, itUser->second.Y),
                   5, color_array.at(itUser->first % color_array.size()), 3, 8);

            /*设置不同手部的深度*/
            hand_depth.at(itUser->first % MAX_HANDS_COLOR) = (unsigned int)(itUser->second.Z* DEPTH_SCALE_FACTOR);//itUser->first会导致程序出现bug

            /*设置不同手部的不同感兴趣区域*/
            hands_roi.at(itUser->first % MAX_HANDS_NUMBER) = Rect(itUser->second.X - ROI_HAND_WIDTH/2, itUser->second.Y - ROI_HAND_HEIGHT/2,
                                               ROI_HAND_WIDTH, ROI_HAND_HEIGHT);
            hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x =  itUser->second.X - ROI_HAND_WIDTH/2;
            hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y =  itUser->second.Y - ROI_HAND_HEIGHT/2;
            hands_roi.at(itUser->first % MAX_HANDS_NUMBER).width = ROI_HAND_WIDTH;
            hands_roi.at(itUser->first % MAX_HANDS_NUMBER).height = ROI_HAND_HEIGHT;
            if(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x <= 0)
                hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x  = 0;
            if(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x > XRES)
                hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x =  XRES;
            if(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y <= 0)
                hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y = 0;
            if(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y > YRES)
                hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y =  YRES;
        }
        imshow("color image", color_image);

        /*获取并显示深度图像*/
        Mat depth_image_src(openni.depth_metadata_.YRes(), openni.depth_metadata_.XRes(),
                            CV_16UC1, (char *)openni.depth_metadata_.Data());//因为kinect获取到的深度图像实际上是无符号的16位数据
        Mat depth_image;
        depth_image_src.convertTo(depth_image, CV_8U, DEPTH_SCALE_FACTOR);
        imshow("depth image", depth_image);

        //取出手的mask部分
        //不管原图像时多少通道的，mask矩阵声明为单通道就ok
        for(auto itUser = openni.hand_points_.cbegin(); itUser != openni.hand_points_.cend(); ++itUser) {
            for(int i = hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x; i < std::min(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x+hands_roi.at(itUser->first % MAX_HANDS_NUMBER).width, XRES); i++)
                for(int j = hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y; j < std::min(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y+hands_roi.at(itUser->first % MAX_HANDS_NUMBER).height, YRES); j++) {
                    hand_segment_mask.at<unsigned char>(j, i) = ((hand_depth.at(itUser->first % MAX_HANDS_NUMBER)-DEPTH_SEGMENT_THRESH) < depth_image.at<unsigned char>(j, i))
                                                                & ((hand_depth.at(itUser->first % MAX_HANDS_NUMBER)+DEPTH_SEGMENT_THRESH) > depth_image.at<unsigned char>(j,i));
                }
         }
        medianBlur(hand_segment_mask, hand_segment_mask, MEDIAN_BLUR_K);
        Mat hand_segment(color_image.size(), CV_8UC3);
        color_image.copyTo(hand_segment, hand_segment_mask);

        /*对mask图像进行轮廓提取,并在手势识别图像中画出来*/
        std::vector< std::vector<Point> > contours;
        findContours(hand_segment_mask, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);//找出mask图像的轮廓
        Mat hand_recognition_image = Mat::zeros(color_image.rows, color_image.cols, CV_8UC3);

        for(int i = 0; i < contours.size(); i++) {  //只有在检测到轮廓时才会去求它的多边形，凸包集，凹陷集
            recognition_flag = true;
            /*找出轮廓图像多边形拟合曲线*/
            Mat contour_mat = Mat(contours[i]);
            if(contourArea(contour_mat) > HAND_LIKELY_AREA) {   //比较有可能像手的区域
                std::vector<Point> approx_poly_curve;
                approxPolyDP(contour_mat, approx_poly_curve, 10, true);//找出轮廓的多边形拟合曲线
                std::vector< std::vector<Point> > approx_poly_curve_debug;
                approx_poly_curve_debug.push_back(approx_poly_curve);

                 drawContours(hand_recognition_image, contours, i, Scalar(255, 0, 0), 1, 8); //画出轮廓
    //            drawContours(hand_recognition_image, approx_poly_curve_debug, 0, Scalar(256, 128, 128), 1, 8); //画出多边形拟合曲线

                /*对求出的多边形拟合曲线求出其凸包集*/
                vector<int> hull;
                convexHull(Mat(approx_poly_curve), hull, true);
                for(int i = 0; i < hull.size(); i++) {
                    circle(hand_recognition_image, approx_poly_curve[hull[i]], 2, Scalar(0, 255, 0), 2, 8);

                    /*统计在中心点1以上凸点的个数*/
                    if(approx_poly_curve[hull[i]].y <= point_y1) {
                        /*统计凸点与中心点1的y轴距离*/
                        long dis_point1 = abs(long(point_y1 - approx_poly_curve[hull[i]].y));
                        int dis1 = point_y1 - approx_poly_curve[hull[i]].y;
                        if(dis_point1 > SEGMENT_POINT1_DISTANCE && dis1 >= 0)  {
                            convex_assist_above_point1++;
                        }
                        convex_number_above_point1++;
                    }

                    /*统计在中心点2以上凸点的个数*/
                    if(approx_poly_curve[hull[i]].y <= point_y2)    {
                        /*统计凸点与中心点1的y轴距离*/
                        long dis_point2 = abs(long(point_y2 - approx_poly_curve[hull[i]].y));
                        int dis2 = point_y2 - approx_poly_curve[hull[i]].y;
                        if(dis_point2 > SEGMENT_POINT2_DISTANCE && dis2 >= 0)  {
                            convex_assist_above_point2++;
                        }
                        convex_number_above_point2++;
                    }
                }

    //            /*对求出的多边形拟合曲线求出凹陷集*/
                std::vector<Vec4i> convexity_defects;
                if(Mat(approx_poly_curve).checkVector(2, CV_32S) > 3)
                    convexityDefects(approx_poly_curve, Mat(hull), convexity_defects);
                for(int i = 0; i < convexity_defects.size(); i++) {
                    circle(hand_recognition_image, approx_poly_curve[convexity_defects[i][2]] , 2, Scalar(0, 0, 255), 2, 8);

                    /*统计在中心点1以上凹陷点的个数*/
                    if(approx_poly_curve[convexity_defects[i][2]].y <= point_y1)
                        concave_number_above_point1++;

                    /*统计在中心点2以上凹陷点的个数*/
                    if(approx_poly_curve[convexity_defects[i][2]].y <= point_y2)
                        concave_number_above_point2++;
                }
            }
        }

        /**画出手势的中心点**/
        for(auto itUser = openni.hand_points_.cbegin(); itUser != openni.hand_points_.cend(); ++itUser) {
            circle(hand_recognition_image, Point(itUser->second.X, itUser->second.Y), 3, Scalar(0, 255, 255), 3, 8);
            circle(hand_recognition_image, Point(itUser->second.X, itUser->second.Y + 25), 3, Scalar(255, 0, 255), 3, 8);
        }

        /*手势数字0~5的识别*/
        //"0"的识别
        if((convex_assist_above_point1 ==0 && convex_number_above_point2 >= 2 && convex_number_above_point2 <= 3 &&
                concave_number_above_point2 <= 1 && concave_number_above_point1 <= 1) || (concave_number_above_point1 ==0
                || concave_number_above_point2 == 0) && recognition_flag == true)
            number_result = 0;
        //"1"的识别
        if(convex_assist_above_point1 ==1 && convex_number_above_point1 >=1  && convex_number_above_point1 <=2 &&
                convex_number_above_point2 >=2 && convex_assist_above_point2 == 1)
            number_result = 1;
        //"2"的识别
        if(convex_number_above_point1 == 2 && concave_number_above_point1 == 1 && convex_assist_above_point2 == 2
                /*convex_assist_above_point1 <=1*/ && concave_number_above_point2 == 1)
            number_result = 2;
        //"3"的识别
        if(convex_number_above_point1 == 3 && concave_number_above_point1 <= 3 &&
                concave_number_above_point1 >=1 && convex_number_above_point2 >= 3 && convex_number_above_point2 <= 4 &&
                convex_assist_above_point2 == 3)
            number_result = 3;
        //"4"的识别
        if(convex_number_above_point1 == 4 && concave_number_above_point1 <=3 && concave_number_above_point1 >=2 &&
                convex_number_above_point2 == 4)
            number_result = 4;
        //"5"的识别
        if(convex_number_above_point1 >=4 && convex_number_above_point2 == 5 && concave_number_above_point2 >= 3 &&
                convex_number_above_point2 >= 4)
            number_result = 5;
        if(number_result !=0 && number_result != 1  && number_result != 2 && number_result != 3 && number_result != 4 && number_result != 5)
            number_result == -1;

        /*在手势识别图上显示匹配的数字*/
        std::stringstream number_str;
        number_str << number_result;
        putText(hand_recognition_image, "Match: ", Point(0, 60), 4, 1, Scalar(0, 255, 0), 2, 0 );
        if(number_result == -1)
            putText(hand_recognition_image, " ", Point(120, 60), 4, 2, Scalar(255, 0 ,0), 2, 0);
        else
            putText(hand_recognition_image, number_str.str(), Point(150, 60), 4, 2, Scalar(255, 0 ,0), 2, 0);

        imshow("handrecognition", hand_recognition_image);
        imshow("hand_segment", hand_segment);

        /*一个循环中对有些变量进行初始化操作*/
        convex_number_above_point1 = 0;
        convex_number_above_point2 = 0;
        concave_number_above_point1 = 0;
        concave_number_above_point2 = 0;
        convex_assist_above_point1 = 0;
        convex_assist_above_point2 = 0;
        number_result = -1;
        recognition_flag = false;
        number_str.clear();

        waitKey(20);
    }

}

#ifndef COPENNI_H
#define COPENNI_H

#include <XnCppWrapper.h>
#include <XnCyclicStackT.h>
#include <XnHashT.h>
#include <XnListT.h>
#include <iostream>
#include <map>

using namespace xn;
using namespace std;

class COpenNI
{
public:
    COpenNI();
    ~COpenNI();

    /*OpenNI的内部初始化，属性设置*/
    bool Initial();

    /*启动OpenNI读取Kinect数据*/
    bool Start();

    /*更新OpenNI读取到的数据*/
    bool UpdateData();

    /*得到色彩图像的node*/
    ImageGenerator& getImageGenerator();

    /*得到深度图像的node*/
    DepthGenerator& getDepthGenerator();

    /*得到人体的node*/
    UserGenerator& getUserGenerator();

    /*得到手势姿势的node*/
    GestureGenerator& getGestureGenerator();

    /*得到手部的node*/
    HandsGenerator& getHandGenerator();

    DepthMetaData depth_metadata_;   //返回深度图像数据
    ImageMetaData image_metadata_;   //返回彩色图像数据
    std::map<XnUserID, XnPoint3D> hand_points_;  //为了存储不同手的实时点而设置的
    std::map< XnUserID, vector<XnPoint3D> > hands_track_points_; //为了绘画后面不同手部的跟踪轨迹而设定的

private:
    /*该函数返回真代表出现了错误，返回假代表正确*/
    bool CheckError(const char* error);

    /*表示有人体进入的回调函数*/
    static void XN_CALLBACK_TYPE CBNewUser(UserGenerator &generator, XnUserID user, void *p_cookie);

    /*表示骨骼校正完成的回调函数*/
    static void XN_CALLBACK_TYPE CBCalibrationComplete(SkeletonCapability &skeleton,
                                                       XnUserID user, XnCalibrationStatus calibration_error, void *p_cookie);

    /*表示某个手势动作已经完成检测的回调函数*/
    static void XN_CALLBACK_TYPE  CBGestureRecognized(xn::GestureGenerator &generator, const XnChar *strGesture,
                                                      const XnPoint3D *pIDPosition, const XnPoint3D *pEndPosition,
                                                      void *pCookie);

    /*表示检测到某个手势开始的回调函数*/
    static void XN_CALLBACK_TYPE CBGestureProgress(xn::GestureGenerator &generator, const XnChar *strGesture,
                                                   const XnPoint3D *pPosition, XnFloat fProgress, void *pCookie);

    /*手部开始建立的回调函数*/
    static void XN_CALLBACK_TYPE HandCreate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition,
                                            XnFloat fTime, void* pCookie);

    /*手部开始更新的回调函数*/
    static void XN_CALLBACK_TYPE HandUpdate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition, XnFloat fTime,
                                            void* pCookie);

    /*手部销毁的回调函数*/
    static void XN_CALLBACK_TYPE HandDestroy(HandsGenerator& rHands, XnUserID xUID, XnFloat fTime, void* pCookie);

    XnStatus status_;
    Context context_;
    XnMapOutputMode xmode_;
    UserGenerator user_generator_;
    ImageGenerator  image_generator_;
    DepthGenerator  depth_generator_;
    GestureGenerator gesture_generator_;
    HandsGenerator  hand_generator_;
};

#endif // COPENNI_H

#include "copenni.h"
#include <XnCppWrapper.h>
#include <iostream>
#include <map>

using namespace xn;
using namespace std;

COpenNI::COpenNI()
{
}

COpenNI::~COpenNI()
{
}

bool COpenNI::Initial()
{
    status_ = context_.Init();
    if(CheckError("Context initial failed!")) {
        return false;
    }

    context_.SetGlobalMirror(true);//设置镜像
    xmode_.nXRes = 640;
    xmode_.nYRes = 480;
    xmode_.nFPS = 30;

    //产生颜色node
    status_ = image_generator_.Create(context_);
    if(CheckError("Create image generator  error!")) {
        return false;
    }

    //设置颜色图片输出模式
    status_ = image_generator_.SetMapOutputMode(xmode_);
    if(CheckError("SetMapOutputMdoe error!")) {
        return false;
    }

    //产生深度node
    status_ = depth_generator_.Create(context_);
    if(CheckError("Create depth generator  error!")) {
        return false;
    }

    //设置深度图片输出模式
    status_ = depth_generator_.SetMapOutputMode(xmode_);
    if(CheckError("SetMapOutputMdoe error!")) {
        return false;
    }

    //产生手势node
    status_ = gesture_generator_.Create(context_);
    if(CheckError("Create gesture generator error!")) {
        return false;
    }

    /*添加手势识别的种类*/
    gesture_generator_.AddGesture("Wave", NULL);
    gesture_generator_.AddGesture("click", NULL);
    gesture_generator_.AddGesture("RaiseHand", NULL);
    gesture_generator_.AddGesture("MovingHand", NULL);

    //产生手部的node
    status_ = hand_generator_.Create(context_);
    if(CheckError("Create hand generaotr error!")) {
        return false;
    }

    //产生人体node
    status_ = user_generator_.Create(context_);
    if(CheckError("Create gesturen generator error!")) {
        return false;
    }

    //视角校正
    status_ = depth_generator_.GetAlternativeViewPointCap().SetViewPoint(image_generator_);
    if(CheckError("Can't set the alternative view point on depth generator!")) {
        return false;
    }

    //设置与手势有关的回调函数
    XnCallbackHandle gesture_cb;
    gesture_generator_.RegisterGestureCallbacks(CBGestureRecognized, CBGestureProgress, this, gesture_cb);

    //设置于手部有关的回调函数
    XnCallbackHandle hands_cb;
    hand_generator_.RegisterHandCallbacks(HandCreate, HandUpdate, HandDestroy, this, hands_cb);

    //设置有人进入视野的回调函数
    XnCallbackHandle new_user_handle;
    user_generator_.RegisterUserCallbacks(CBNewUser, NULL, NULL, new_user_handle);
    user_generator_.GetSkeletonCap().SetSkeletonProfile(XN_SKEL_PROFILE_ALL);//设定使用所有关节（共15个）

    //设置骨骼校正完成的回调函数
    XnCallbackHandle calibration_complete;
    user_generator_.GetSkeletonCap().RegisterToCalibrationComplete(CBCalibrationComplete, this, calibration_complete);
    return true;
}

bool COpenNI::Start()
{
    status_ = context_.StartGeneratingAll();
    if(CheckError("Start generating error!")) {
        return false;
    }
    return true;
}

bool COpenNI::UpdateData()
{
    status_ = context_.WaitNoneUpdateAll();
    if(CheckError("Update date error!")) {
        return false;
    }
    //获取数据
    image_generator_.GetMetaData(image_metadata_);
    depth_generator_.GetMetaData(depth_metadata_);

    return true;
}

ImageGenerator &COpenNI::getImageGenerator()
{
    return image_generator_;
}

DepthGenerator &COpenNI::getDepthGenerator()
{
    return depth_generator_;
}

UserGenerator &COpenNI::getUserGenerator()
{
    return user_generator_;
}

GestureGenerator &COpenNI::getGestureGenerator()
{
    return gesture_generator_;
}

HandsGenerator &COpenNI::getHandGenerator()
{
    return hand_generator_;
}

bool COpenNI::CheckError(const char *error)
{
    if(status_ != XN_STATUS_OK) {
        cerr << error << ": " << xnGetStatusString( status_ ) << endl;
        return true;
    }
    return false;
}

void COpenNI::CBNewUser(UserGenerator &generator, XnUserID user, void *p_cookie)
{
    //得到skeleton的capability,并调用RequestCalibration函数设置对新检测到的人进行骨骼校正
    generator.GetSkeletonCap().RequestCalibration(user, true);
}

void COpenNI::CBCalibrationComplete(SkeletonCapability &skeleton, XnUserID user, XnCalibrationStatus calibration_error, void *p_cookie)
{
    if(calibration_error == XN_CALIBRATION_STATUS_OK) {
        skeleton.StartTracking(user);//骨骼校正完成后就开始进行人体跟踪了
    }
    else {
        UserGenerator *p_user = (UserGenerator*)p_cookie;
        skeleton.RequestCalibration(user, true);//骨骼校正失败时重新设置对人体骨骼继续进行校正
    }
}

void COpenNI::CBGestureRecognized(GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pIDPosition, const XnPoint3D *pEndPosition, void *pCookie)
{
    COpenNI *openni = (COpenNI*)pCookie;
    openni->hand_generator_.StartTracking(*pEndPosition);
}

void COpenNI::CBGestureProgress(GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pPosition, XnFloat fProgress, void *pCookie)
{
}

void COpenNI::HandCreate(HandsGenerator &rHands, XnUserID xUID, const XnPoint3D *pPosition, XnFloat fTime, void *pCookie)
{
    COpenNI *openni = (COpenNI*)pCookie;
    XnPoint3D project_pos;
    openni->depth_generator_.ConvertRealWorldToProjective(1, pPosition, &project_pos);
    pair<XnUserID, XnPoint3D> hand_point_pair(xUID, XnPoint3D());//在进行pair类型的定义时，可以将第2个设置为空
    hand_point_pair.second = project_pos;
    openni->hand_points_.insert(hand_point_pair);//将检测到的手部存入map类型的hand_points_中。

    pair<XnUserID, vector<XnPoint3D>> hand_track_point(xUID, vector<XnPoint3D>());
    hand_track_point.second.push_back(project_pos);
    openni->hands_track_points_.insert(hand_track_point);
}

void COpenNI::HandUpdate(HandsGenerator &rHands, XnUserID xUID, const XnPoint3D *pPosition, XnFloat fTime, void *pCookie)
{
    COpenNI *openni = (COpenNI*)pCookie;
    XnPoint3D project_pos;
    openni->depth_generator_.ConvertRealWorldToProjective(1, pPosition, &project_pos);
    openni->hand_points_.find(xUID)->second = project_pos;
    openni->hands_track_points_.find(xUID)->second.push_back(project_pos);
}

void COpenNI::HandDestroy(HandsGenerator &rHands, XnUserID xUID, XnFloat fTime, void *pCookie)
{
    COpenNI *openni = (COpenNI*)pCookie;
    openni->hand_points_.erase(openni->hand_points_.find(xUID));
    openni->hands_track_points_.erase(openni->hands_track_points_.find(xUID ));
}

typedef    unsigned int              XnUInt32;

typedef XnUInt32 XnUserID;

#ifndef COpenniHand_H
#define COpenniHand_H

#include <XnCppWrapper.h>
#include <iostream>
#include <vector>
#include <map>

using namespace xn;
using namespace std;

class COpenniHand
{
public:
    COpenniHand();
    ~COpenniHand();

    /*OpenNI的内部初始化，属性设置*/
    bool Initial();

    /*启动OpenNI读取Kinect数据*/
    bool Start();

    /*更新OpenNI读取到的数据*/
    bool UpdateData();

    /*得到色彩图像的node*/
    ImageGenerator& getImageGenerator();

    /*得到深度图像的node*/
    DepthGenerator& getDepthGenerator();

    /*得到手势姿势的node*/
    GestureGenerator& getGestureGenerator();

    /*得到手部的node*/
    HandsGenerator& getHandGenerator();
    DepthMetaData depth_metadata_;   //返回深度图像数据
    ImageMetaData image_metadata_;   //返回彩色图像数据
    std::map<XnUserID, XnPoint3D> hand_points_;  //为了存储不同手的实时点而设置的
    std::map< XnUserID, vector<XnPoint3D> > hands_track_points_; //为了绘画后面不同手部的跟踪轨迹而设定的

private:
    /*该函数返回真代表出现了错误，返回假代表正确*/
    bool CheckError(const char* error);

    /*表示某个手势动作已经完成检测的回调函数*/
    static void XN_CALLBACK_TYPE  CBGestureRecognized(xn::GestureGenerator &generator, const XnChar *strGesture,
                                                      const XnPoint3D *pIDPosition, const XnPoint3D *pEndPosition,
                                                      void *pCookie);

    /*表示检测到某个手势开始的回调函数*/
    static void XN_CALLBACK_TYPE CBGestureProgress(xn::GestureGenerator &generator, const XnChar *strGesture,
                                                   const XnPoint3D *pPosition, XnFloat fProgress, void *pCookie);

    /*手部开始建立的回调函数*/
    static void XN_CALLBACK_TYPE HandCreate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition,
                                            XnFloat fTime, void* pCookie);

    /*手部开始更新的回调函数*/
    static void XN_CALLBACK_TYPE HandUpdate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition, XnFloat fTime,
                                            void* pCookie);

    /*手部销毁的回调函数*/
    static void XN_CALLBACK_TYPE HandDestroy(HandsGenerator& rHands, XnUserID xUID, XnFloat fTime, void* pCookie);

    XnStatus status_;
    Context context_;
    XnMapOutputMode xmode_;
    ImageGenerator  image_generator_;
    DepthGenerator  depth_generator_;
    GestureGenerator gesture_generator_;
    HandsGenerator  hand_generator_;
};

#endif // COpenniHand_H

#include "copennihand.h"
#include <XnCppWrapper.h>
#include <iostream>
#include <map>

using namespace xn;
using namespace std;

COpenniHand::COpenniHand()
{
}

COpenniHand::~COpenniHand()
{
}

bool COpenniHand::Initial()
{
    status_ = context_.Init();
    if(CheckError("Context initial failed!")) {
        return false;
    }

    context_.SetGlobalMirror(true);//设置镜像
    xmode_.nXRes = 640;
    xmode_.nYRes = 480;
    xmode_.nFPS = 30;

    //产生颜色node
    status_ = image_generator_.Create(context_);
    if(CheckError("Create image generator  error!")) {
        return false;
    }

    //设置颜色图片输出模式
    status_ = image_generator_.SetMapOutputMode(xmode_);
    if(CheckError("SetMapOutputMdoe error!")) {
        return false;
    }

    //产生深度node
    status_ = depth_generator_.Create(context_);
    if(CheckError("Create depth generator  error!")) {
        return false;
    }

    //设置深度图片输出模式
    status_ = depth_generator_.SetMapOutputMode(xmode_);
    if(CheckError("SetMapOutputMdoe error!")) {
        return false;
    }

    //产生手势node
    status_ = gesture_generator_.Create(context_);
    if(CheckError("Create gesture generator error!")) {
        return false;
    }

    /*添加手势识别的种类*/
    gesture_generator_.AddGesture("Wave", NULL);
    gesture_generator_.AddGesture("click", NULL);
    gesture_generator_.AddGesture("RaiseHand", NULL);
    gesture_generator_.AddGesture("MovingHand", NULL);

    //产生手部的node
    status_ = hand_generator_.Create(context_);
    if(CheckError("Create hand generaotr error!")) {
        return false;
    }

    //视角校正
    status_ = depth_generator_.GetAlternativeViewPointCap().SetViewPoint(image_generator_);
    if(CheckError("Can't set the alternative view point on depth generator!")) {
        return false;
    }

    //设置与手势有关的回调函数
    XnCallbackHandle gesture_cb;
    gesture_generator_.RegisterGestureCallbacks(CBGestureRecognized, CBGestureProgress, this, gesture_cb);

    //设置于手部有关的回调函数
    XnCallbackHandle hands_cb;
    hand_generator_.RegisterHandCallbacks(HandCreate, HandUpdate, HandDestroy, this, hands_cb);

    return true;
}

bool COpenniHand::Start()
{
    status_ = context_.StartGeneratingAll();
    if(CheckError("Start generating error!")) {
        return false;
    }
    return true;
}

bool COpenniHand::UpdateData()
{
    status_ = context_.WaitNoneUpdateAll();
    if(CheckError("Update date error!")) {
        return false;
    }
    //获取数据
    image_generator_.GetMetaData(image_metadata_);
    depth_generator_.GetMetaData(depth_metadata_);

    return true;
}

ImageGenerator &COpenniHand::getImageGenerator()
{
    return image_generator_;
}

DepthGenerator &COpenniHand::getDepthGenerator()
{
    return depth_generator_;
}

GestureGenerator &COpenniHand::getGestureGenerator()
{
    return gesture_generator_;
}

HandsGenerator &COpenniHand::getHandGenerator()
{
    return hand_generator_;
}

bool COpenniHand::CheckError(const char *error)
{
    if(status_ != XN_STATUS_OK) {
        cerr << error << ": " << xnGetStatusString( status_ ) << endl;
        return true;
    }
    return false;
}

void COpenniHand::CBGestureRecognized(GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pIDPosition, const XnPoint3D *pEndPosition, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    openni->hand_generator_.StartTracking(*pEndPosition);
}

void COpenniHand::CBGestureProgress(GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pPosition, XnFloat fProgress, void *pCookie)
{
}

void COpenniHand::HandCreate(HandsGenerator &rHands, XnUserID xUID, const XnPoint3D *pPosition, XnFloat fTime, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    XnPoint3D project_pos;
    openni->depth_generator_.ConvertRealWorldToProjective(1, pPosition, &project_pos);
    pair<XnUserID, XnPoint3D> hand_point_pair(xUID, XnPoint3D());//在进行pair类型的定义时，可以将第2个设置为空
    hand_point_pair.second = project_pos;
    openni->hand_points_.insert(hand_point_pair);//将检测到的手部存入map类型的hand_points_中。

    pair<XnUserID, vector<XnPoint3D>> hand_track_point(xUID, vector<XnPoint3D>());
    hand_track_point.second.push_back(project_pos);
    openni->hands_track_points_.insert(hand_track_point);
}

void COpenniHand::HandUpdate(HandsGenerator &rHands, XnUserID xUID, const XnPoint3D *pPosition, XnFloat fTime, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    XnPoint3D project_pos;
    openni->depth_generator_.ConvertRealWorldToProjective(1, pPosition, &project_pos);
    openni->hand_points_.find(xUID)->second = project_pos;
    openni->hands_track_points_.find(xUID)->second.push_back(project_pos);
}

void COpenniHand::HandDestroy(HandsGenerator &rHands, XnUserID xUID, XnFloat fTime, void *pCookie)
{
    COpenniHand *openni = (COpenniHand*)pCookie;
    openni->hand_points_.erase(openni->hand_points_.find(xUID));
    openni->hands_track_points_.erase(openni->hands_track_points_.find(xUID ));
}

#include <iostream>

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <opencv2/core/core.hpp>
#include "copennihand.h"

#include <iostream>

#define DEPTH_SCALE_FACTOR 255./4096.
#define ROI_HAND_WIDTH 140
#define ROI_HAND_HEIGHT 140
#define MEDIAN_BLUR_K 5
#define XRES  640
#define YRES  480
#define DEPTH_SEGMENT_THRESH 5
#define MAX_HANDS_COLOR 10
#define MAX_HANDS_NUMBER  10

using namespace cv;
using namespace xn;
using namespace std;

int main (int argc, char **argv)
{
    vector<Scalar> color_array;//采用默认的10种颜色
    {
        color_array.push_back(Scalar(255, 0, 0));
        color_array.push_back(Scalar(0, 255, 0));
        color_array.push_back(Scalar(0, 0, 255));
        color_array.push_back(Scalar(255, 0, 255));
        color_array.push_back(Scalar(255, 255, 0));
        color_array.push_back(Scalar(0, 255, 255));
        color_array.push_back(Scalar(128, 255, 0));
        color_array.push_back(Scalar(0, 128, 255));
        color_array.push_back(Scalar(255, 0, 128));
        color_array.push_back(Scalar(255, 128, 255));
    }
    vector<unsigned int> hand_depth(MAX_HANDS_NUMBER, 0);
    vector<Rect> hands_roi(MAX_HANDS_NUMBER, Rect(XRES/2, YRES/2, ROI_HAND_WIDTH, ROI_HAND_HEIGHT));

    namedWindow("color image", CV_WINDOW_AUTOSIZE);
    namedWindow("depth image", CV_WINDOW_AUTOSIZE);
    namedWindow("hand_segment", CV_WINDOW_AUTOSIZE);//显示分割出来的手的区域

    COpenniHand openni;
    if(!openni.Initial())
        return 1;

    if(!openni.Start())
        return 1;
    while(1) {
        if(!openni.UpdateData()) {
            return 1;
        }
        /*获取并显示色彩图像*/
        Mat color_image_src(openni.image_metadata_.YRes(), openni.image_metadata_.XRes(),
                            CV_8UC3, (char *)openni.image_metadata_.Data());
        Mat color_image;
        cvtColor(color_image_src, color_image, CV_RGB2BGR);

        for(auto itUser = openni.hand_points_.cbegin(); itUser != openni.hand_points_.cend(); ++itUser) {

            circle(color_image, Point(itUser->second.X, itUser->second.Y),
                   5, color_array.at(itUser->first % color_array.size()), 3, 8);

            /*设置不同手部的深度*/
            hand_depth.at(itUser->first % MAX_HANDS_COLOR) = (unsigned int)(itUser->second.Z* DEPTH_SCALE_FACTOR);//itUser->first会导致程序出现bug

            /*设置不同手部的不同感兴趣区域*/
            hands_roi.at(itUser->first % MAX_HANDS_NUMBER) = Rect(itUser->second.X - ROI_HAND_WIDTH/2, itUser->second.Y - ROI_HAND_HEIGHT/2,
                                               ROI_HAND_WIDTH, ROI_HAND_HEIGHT);
            hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x =  itUser->second.X - ROI_HAND_WIDTH/2;
            hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y =  itUser->second.Y - ROI_HAND_HEIGHT/2;
            hands_roi.at(itUser->first % MAX_HANDS_NUMBER).width = ROI_HAND_WIDTH;
            hands_roi.at(itUser->first % MAX_HANDS_NUMBER).height = ROI_HAND_HEIGHT;
            if(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x <= 0)
                hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x  = 0;
            if(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x > XRES)
                hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x =  XRES;
            if(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y <= 0)
                hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y = 0;
            if(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y > YRES)
                hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y =  YRES;
        }
        imshow("color image", color_image);

        /*获取并显示深度图像*/
        Mat depth_image_src(openni.depth_metadata_.YRes(), openni.depth_metadata_.XRes(),
                            CV_16UC1, (char *)openni.depth_metadata_.Data());//因为kinect获取到的深度图像实际上是无符号的16位数据
        Mat depth_image;
        depth_image_src.convertTo(depth_image, CV_8U, DEPTH_SCALE_FACTOR);
        imshow("depth image", depth_image);

        //取出手的mask部分
        //不管原图像时多少通道的，mask矩阵声明为单通道就ok
        Mat hand_segment_mask(depth_image.size(), CV_8UC1, Scalar::all(0));
        for(auto itUser = openni.hand_points_.cbegin(); itUser != openni.hand_points_.cend(); ++itUser)
            for(int i = hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x; i < std::min(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).x+hands_roi.at(itUser->first % MAX_HANDS_NUMBER).width, XRES); i++)
                for(int j = hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y; j < std::min(hands_roi.at(itUser->first % MAX_HANDS_NUMBER).y+hands_roi.at(itUser->first % MAX_HANDS_NUMBER).height, YRES); j++) {
                    hand_segment_mask.at<unsigned char>(j, i) = ((hand_depth.at(itUser->first % MAX_HANDS_NUMBER)-DEPTH_SEGMENT_THRESH) < depth_image.at<unsigned char>(j, i))
                                                                & ((hand_depth.at(itUser->first % MAX_HANDS_NUMBER)+DEPTH_SEGMENT_THRESH) > depth_image.at<unsigned char>(j,i));
                }
        medianBlur(hand_segment_mask, hand_segment_mask, MEDIAN_BLUR_K);
        Mat hand_segment(color_image.size(), CV_8UC3);
        color_image.copyTo(hand_segment, hand_segment_mask);

        imshow("hand_segment", hand_segment);
        waitKey(30);
    }

}

#ifndef COPENNI_CLASS
#define COPENNI_CLASS

#include <XnCppWrapper.h>
#include <iostream>
#include <map>

using namespace xn;
using namespace std;

class COpenNI
{
public:
    ~COpenNI() {
        context.Release();//释放空间
    }
    bool Initial() {
        //初始化
        status = context.Init();
        if(CheckError("Context initial failed!")) {
            return false;
        }
        context.SetGlobalMirror(true);//设置镜像
        xmode.nXRes = 640;
        xmode.nYRes = 480;
        xmode.nFPS = 30;
        //产生颜色node
        status = image_generator.Create(context);
        if(CheckError("Create image generator  error!")) {
            return false;
        }
        //设置颜色图片输出模式
        status = image_generator.SetMapOutputMode(xmode);
        if(CheckError("SetMapOutputMdoe error!")) {
            return false;
        }
        //产生深度node
        status = depth_generator.Create(context);
        if(CheckError("Create depth generator  error!")) {
            return false;
        }
        //设置深度图片输出模式
        status = depth_generator.SetMapOutputMode(xmode);
        if(CheckError("SetMapOutputMdoe error!")) {
            return false;
        }
        //产生手势node
        status = gesture_generator.Create(context);
        if(CheckError("Create gesture generator error!")) {
            return false;
        }
        /*添加手势识别的种类*/
        gesture_generator.AddGesture("Wave", NULL);
        gesture_generator.AddGesture("click", NULL);
        gesture_generator.AddGesture("RaiseHand", NULL);
        gesture_generator.AddGesture("MovingHand", NULL);
        //产生手部的node
        status = hands_generator.Create(context);
        if(CheckError("Create hand generaotr error!")) {
            return false;
        }
        //产生人体node
        status = user_generator.Create(context);
        if(CheckError("Create gesturen generator error!")) {
            return false;
        }
        //视角校正
        status = depth_generator.GetAlternativeViewPointCap().SetViewPoint(image_generator);
        if(CheckError("Can't set the alternative view point on depth generator!")) {
            return false;
        }
        //设置与手势有关的回调函数
        XnCallbackHandle gesture_cb;
        gesture_generator.RegisterGestureCallbacks(CBGestureRecognized, CBGestureProgress, this, gesture_cb);
        //设置于手部有关的回调函数
        XnCallbackHandle hands_cb;
        hands_generator.RegisterHandCallbacks(HandCreate, HandUpdate, HandDestroy, this, hands_cb);
        //设置有人进入视野的回调函数
        XnCallbackHandle new_user_handle;
        user_generator.RegisterUserCallbacks(CBNewUser, NULL, NULL, new_user_handle);
        user_generator.GetSkeletonCap().SetSkeletonProfile(XN_SKEL_PROFILE_ALL);//设定使用所有关节（共15个）
        //设置骨骼校正完成的回调函数
        XnCallbackHandle calibration_complete;
        user_generator.GetSkeletonCap().RegisterToCalibrationComplete(CBCalibrationComplete, NULL, calibration_complete);
        return true;
    }

    bool Start() {
        status = context.StartGeneratingAll();
        if(CheckError("Start generating error!")) {
            return false;
        }
        return true;
    }

    bool UpdateData() {
        status = context.WaitNoneUpdateAll();
        if(CheckError("Update date error!")) {
            return false;
        }
        //获取数据
        image_generator.GetMetaData(image_metadata);
        depth_generator.GetMetaData(depth_metadata);

        return true;
    }
    //得到色彩图像的node
    ImageGenerator& getImageGenerator() {
        return image_generator;
    }
    //得到深度图像的node
    DepthGenerator& getDepthGenerator() {
        return depth_generator;
    }
    //得到人体的node
    UserGenerator& getUserGenerator() {
        return user_generator;
    }
    //得到手势姿势node
    GestureGenerator& getGestureGenerator() {
        return gesture_generator;
    }

public:
    DepthMetaData depth_metadata;
    ImageMetaData image_metadata;
    DepthGenerator  depth_generator;
    HandsGenerator  hands_generator;
    std::map<XnUserID, XnPoint3D> hand_points;//为了存储不同手的实时点而设置的
    map< XnUserID, vector<XnPoint3D> > hands_track_points;//为了绘画后面不同手部的跟踪轨迹而设定的

private:
    //该函数返回真代表出现了错误，返回假代表正确
    bool CheckError(const char* error) {
        if(status != XN_STATUS_OK ) {
            cerr << error << ": " << xnGetStatusString( status ) << endl;
            return true;
        }
        return false;
    }
    //手势某个动作已经完成检测的回调函数
    static void XN_CALLBACK_TYPE  CBGestureRecognized(xn::GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pIDPosition,
                                                      const XnPoint3D *pEndPosition, void *pCookie) {
        COpenNI *openni = (COpenNI*)pCookie;
        openni->hands_generator.StartTracking(*pIDPosition);
    }
    //手势开始检测的回调函数
    static void XN_CALLBACK_TYPE CBGestureProgress(xn::GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pPosition,
                                                   XnFloat fProgress, void *pCookie) {
        COpenNI *openni = (COpenNI*)pCookie;
        openni->hands_generator.StartTracking(*pPosition);
    }
    //手部开始建立的回调函数
    static void XN_CALLBACK_TYPE HandCreate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition,
                                            XnFloat fTime, void* pCookie) {
        COpenNI *openni = (COpenNI*)pCookie;
        XnPoint3D project_pos;
        openni->depth_generator.ConvertRealWorldToProjective(1, pPosition, &project_pos);
        pair<XnUserID, XnPoint3D> hand_point_pair(xUID, XnPoint3D());//在进行pair类型的定义时，可以将第2个设置为空
        hand_point_pair.second = project_pos;
        openni->hand_points.insert(hand_point_pair);//将检测到的手部存入map类型的hand_points中。

        pair<XnUserID, vector<XnPoint3D>> hand_track_point(xUID, vector<XnPoint3D>());
        hand_track_point.second.push_back(project_pos);
        openni->hands_track_points.insert(hand_track_point);
    }
    //手部开始更新的回调函数
    static void XN_CALLBACK_TYPE HandUpdate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition, XnFloat fTime,
                                            void* pCookie) {
        COpenNI *openni = (COpenNI*)pCookie;
        XnPoint3D project_pos;
        openni->depth_generator.ConvertRealWorldToProjective(1, pPosition, &project_pos);
        openni->hand_points.find(xUID)->second = project_pos;
        openni->hands_track_points.find(xUID)->second.push_back(project_pos);
    }
    //销毁手部的回调函数
    static void XN_CALLBACK_TYPE HandDestroy(HandsGenerator& rHands, XnUserID xUID, XnFloat fTime,
                                              void* pCookie) {
        COpenNI *openni = (COpenNI*)pCookie;
        openni->hand_points.erase(openni->hand_points.find(xUID));
        openni->hands_track_points.erase(openni->hands_track_points.find(xUID));
    }
    //有人进入视野时的回调函数
    static void XN_CALLBACK_TYPE CBNewUser(UserGenerator &generator, XnUserID user, void *p_cookie) {
        //得到skeleton的capability,并调用RequestCalibration函数设置对新检测到的人进行骨骼校正
        generator.GetSkeletonCap().RequestCalibration(user, true);
    }
    //完成骨骼校正的回调函数
    static void XN_CALLBACK_TYPE CBCalibrationComplete(SkeletonCapability &skeleton,
                                                       XnUserID user, XnCalibrationStatus calibration_error, void *p_cookie) {
        if(calibration_error == XN_CALIBRATION_STATUS_OK) {
            skeleton.StartTracking(user);//骨骼校正完成后就开始进行人体跟踪了
        }
        else {
            UserGenerator *p_user = (UserGenerator*)p_cookie;
            skeleton.RequestCalibration(user, true);//骨骼校正失败时重新设置对人体骨骼继续进行校正
        }
    }

private:
    XnStatus status;
    Context context;
    ImageGenerator  image_generator;
    UserGenerator user_generator;
    GestureGenerator gesture_generator;
    XnMapOutputMode xmode;

};

#endif

#include <iostream>

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <opencv2/core/core.hpp>
#include "copenni.cpp"

#include <iostream>

#define DEPTH_SCALE_FACTOR 255./4096.
#define ROI_HAND_WIDTH 140
#define ROI_HAND_HEIGHT 140
#define MEDIAN_BLUR_K 5

int XRES = 640;
int YRES = 480;
#define DEPTH_SEGMENT_THRESH 5

using namespace cv;
using namespace xn;
using namespace std;

int main (int argc, char **argv)
{
    COpenNI openni;
    vector<Scalar> color_array;//采用默认的10种颜色
    {
        color_array.push_back(Scalar(255, 0, 0));
        color_array.push_back(Scalar(0, 255, 0));
        color_array.push_back(Scalar(0, 0, 255));
        color_array.push_back(Scalar(255, 0, 255));
        color_array.push_back(Scalar(255, 255, 0));
        color_array.push_back(Scalar(0, 255, 255));
        color_array.push_back(Scalar(128, 255, 0));
        color_array.push_back(Scalar(0, 128, 255));
        color_array.push_back(Scalar(255, 0, 128));
        color_array.push_back(Scalar(255, 128, 255));
    }
    vector<int> hand_depth(10, 0);
    vector<Rect> hands_roi(10, Rect(320, 240, ROI_HAND_WIDTH, ROI_HAND_HEIGHT));

    if(!openni.Initial())
        return 1;

    namedWindow("color image", CV_WINDOW_AUTOSIZE);
    namedWindow("depth image", CV_WINDOW_AUTOSIZE);
    namedWindow("hand_segment", CV_WINDOW_AUTOSIZE);//显示分割出来的手的区域

    if(!openni.Start())
        return 1;
    while(1) {
        if(!openni.UpdateData()) {
            return 1;
        }
        /*获取并显示色彩图像*/
        Mat color_image_src(openni.image_metadata.YRes(), openni.image_metadata.XRes(),
                            CV_8UC3, (char *)openni.image_metadata.Data());
        Mat color_image;
        cvtColor(color_image_src, color_image, CV_RGB2BGR);
        for(auto itUser = openni.hand_points.cbegin(); itUser != openni.hand_points.cend(); ++itUser) {
            circle(color_image, Point(itUser->second.X, itUser->second.Y),
                   5, color_array.at(itUser->first % color_array.size()), 3, 8);
            /*设置不同手部的深度*/
            hand_depth.at(itUser->first) = itUser->second.Z* DEPTH_SCALE_FACTOR;
            /*设置不同手部的不同感兴趣区域*/
            hands_roi.at(itUser->first) = Rect(itUser->second.X - ROI_HAND_WIDTH/2, itUser->second.Y - ROI_HAND_HEIGHT/2,
                                               ROI_HAND_WIDTH, ROI_HAND_HEIGHT);
            hands_roi.at(itUser->first).x =  itUser->second.X - ROI_HAND_WIDTH/2;
            hands_roi.at(itUser->first).y =  itUser->second.Y - ROI_HAND_HEIGHT/2;
            hands_roi.at(itUser->first).width = ROI_HAND_WIDTH;
            hands_roi.at(itUser->first).height = ROI_HAND_HEIGHT;
            if(hands_roi.at(itUser->first).x <= 0)
                hands_roi.at(itUser->first).x  = 0;
            if(hands_roi.at(itUser->first).x > XRES)
                hands_roi.at(itUser->first).x =  XRES;
            if(hands_roi.at(itUser->first).y <= 0)
                hands_roi.at(itUser->first).y = 0;
            if(hands_roi.at(itUser->first).y > YRES)
                hands_roi.at(itUser->first).y =  YRES;
        }

        imshow("color image", color_image);

        /*获取并显示深度图像*/
        Mat depth_image_src(openni.depth_metadata.YRes(), openni.depth_metadata.XRes(),
                            CV_16UC1, (char *)openni.depth_metadata.Data());//因为kinect获取到的深度图像实际上是无符号的16位数据
        Mat depth_image;
        depth_image_src.convertTo(depth_image, CV_8U, DEPTH_SCALE_FACTOR);
        imshow("depth image", depth_image);

        //取出手的mask部分
        //不管原图像时多少通道的，mask矩阵声明为单通道就ok
        Mat hand_segment_mask(depth_image.size(), CV_8UC1, Scalar::all(0));
        for(auto itUser = openni.hand_points.cbegin(); itUser != openni.hand_points.cend(); ++itUser)
            for(int i = hands_roi.at(itUser->first).x; i < std::min(hands_roi.at(itUser->first).x+hands_roi.at(itUser->first).width, XRES); i++)
                for(int j = hands_roi.at(itUser->first).y; j < std::min(hands_roi.at(itUser->first).y+hands_roi.at(itUser->first).height, YRES); j++) {
                    hand_segment_mask.at<unsigned char>(j, i) = ((hand_depth.at(itUser->first)-DEPTH_SEGMENT_THRESH) < depth_image.at<unsigned char>(j, i))
                                                                & ((hand_depth.at(itUser->first)+DEPTH_SEGMENT_THRESH) > depth_image.at<unsigned char>(j,i));
                }
        medianBlur(hand_segment_mask, hand_segment_mask, MEDIAN_BLUR_K);
        Mat hand_segment(color_image.size(), CV_8UC3);
        color_image.copyTo(hand_segment, hand_segment_mask);

        imshow("hand_segment", hand_segment);
        waitKey(30);
    }

}

#include <iostream>

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <opencv2/core/core.hpp>
#include "copenni.cpp"

#include <iostream>

#define DEPTH_SCALE_FACTOR 255./4096.
#define ROI_HAND_WIDTH 140
#define ROI_HAND_HEIGHT 140
#define MEDIAN_BLUR_K 5

int XRES = 640;
int YRES = 480;
#define DEPTH_SEGMENT_THRESH 5

using namespace cv;
using namespace xn;
using namespace std;

int main (int argc, char **argv)
{
    COpenNI openni;
    int hand_depth;
    Rect roi;
    roi.x = XRES/2;
    roi.y = YRES/2;
    roi.width = ROI_HAND_WIDTH;
    roi.height = ROI_HAND_HEIGHT;
    if(!openni.Initial())
        return 1;

    namedWindow("color image", CV_WINDOW_AUTOSIZE);
    namedWindow("depth image", CV_WINDOW_AUTOSIZE);
    namedWindow("hand_segment", CV_WINDOW_AUTOSIZE);//显示分割出来的手的区域

    if(!openni.Start())
        return 1;
    while(1) {
        if(!openni.UpdateData()) {
            return 1;
        }
        /*获取并显示色彩图像*/
        Mat color_image_src(openni.image_metadata.YRes(), openni.image_metadata.XRes(),
                            CV_8UC3, (char *)openni.image_metadata.Data());
        Mat color_image;
        cvtColor(color_image_src, color_image, CV_RGB2BGR);
        circle(color_image, Point(hand_point.X, hand_point.Y), 5, Scalar(255, 0, 0), 3, 8);
        imshow("color image", color_image);

        /*获取并显示深度图像*/
        Mat depth_image_src(openni.depth_metadata.YRes(), openni.depth_metadata.XRes(),
                            CV_16UC1, (char *)openni.depth_metadata.Data());//因为kinect获取到的深度图像实际上是无符号的16位数据
        Mat depth_image;
        depth_image_src.convertTo(depth_image, CV_8U, DEPTH_SCALE_FACTOR);
        imshow("depth image", depth_image);

        /*下面的代码是提取手的轮廓部分*/
        hand_depth = hand_point.Z * DEPTH_SCALE_FACTOR;
        roi.x = hand_point.X - ROI_HAND_WIDTH/2;
        roi.y = hand_point.Y - ROI_HAND_HEIGHT/2;
        if(roi.x <= 0)
            roi.x = 0;
        if(roi.x >= XRES)
            roi.x = XRES;
        if(roi.y <=0 )
            roi.y = 0;
        if(roi.y >= YRES)
            roi.y = YRES;

        //取出手的mask部分
        //不管原图像时多少通道的，mask矩阵声明为单通道就ok
        Mat hand_segment_mask(depth_image.size(), CV_8UC1, Scalar::all(0));
        for(int i = roi.x; i < std::min(roi.x+roi.width, XRES); i++)
            for(int j = roi.y; j < std::min(roi.y+roi.height, YRES); j++) {
                hand_segment_mask.at<unsigned char>(j, i) = ((hand_depth-DEPTH_SEGMENT_THRESH) < depth_image.at<unsigned char>(j, i))
                                                            & ((hand_depth+DEPTH_SEGMENT_THRESH) > depth_image.at<unsigned char>(j,i));
            }
        medianBlur(hand_segment_mask, hand_segment_mask, MEDIAN_BLUR_K);
        Mat hand_segment(color_image.size(), CV_8UC3);
        color_image.copyTo(hand_segment, hand_segment_mask);

        imshow("hand_segment", hand_segment);
        waitKey(20);
    }

}

#ifndef COPENNI_CLASS
#define COPENNI_CLASS

#include <XnCppWrapper.h>
#include <iostream>
#include <map>

using namespace xn;
using namespace std;

static DepthGenerator  depth_generator;
static HandsGenerator  hands_generator;
static XnPoint3D hand_point;
static std::map<XnUserID, vector<XnPoint3D>> hands_track_points;

class COpenNI
{
public:
    ~COpenNI() {
        context.Release();//释放空间
    }
    bool Initial() {
        //初始化
        status = context.Init();
        if(CheckError("Context initial failed!")) {
            return false;
        }
        context.SetGlobalMirror(true);//设置镜像
        xmode.nXRes = 640;
        xmode.nYRes = 480;
        xmode.nFPS = 30;
        //产生颜色node
        status = image_generator.Create(context);
        if(CheckError("Create image generator  error!")) {
            return false;
        }
        //设置颜色图片输出模式
        status = image_generator.SetMapOutputMode(xmode);
        if(CheckError("SetMapOutputMdoe error!")) {
            return false;
        }
        //产生深度node
        status = depth_generator.Create(context);
        if(CheckError("Create depth generator  error!")) {
            return false;
        }
        //设置深度图片输出模式
        status = depth_generator.SetMapOutputMode(xmode);
        if(CheckError("SetMapOutputMdoe error!")) {
            return false;
        }
        //产生手势node
        status = gesture_generator.Create(context);
        if(CheckError("Create gesture generator error!")) {
            return false;
        }
        /*添加手势识别的种类*/
        gesture_generator.AddGesture("Wave", NULL);
        gesture_generator.AddGesture("click", NULL);
        gesture_generator.AddGesture("RaiseHand", NULL);
        gesture_generator.AddGesture("MovingHand", NULL);
        //产生手部的node
        status = hands_generator.Create(context);
        if(CheckError("Create hand generaotr error!")) {
            return false;
        }
        //产生人体node
        status = user_generator.Create(context);
        if(CheckError("Create gesturen generator error!")) {
            return false;
        }
        //视角校正
        status = depth_generator.GetAlternativeViewPointCap().SetViewPoint(image_generator);
        if(CheckError("Can't set the alternative view point on depth generator!")) {
            return false;
        }
        //设置与手势有关的回调函数
        XnCallbackHandle gesture_cb;
        gesture_generator.RegisterGestureCallbacks(CBGestureRecognized, CBGestureProgress, NULL, gesture_cb);
        //设置于手部有关的回调函数
        XnCallbackHandle hands_cb;
        hands_generator.RegisterHandCallbacks(HandCreate, HandUpdate, HandDestroy, NULL, hands_cb);
        //设置有人进入视野的回调函数
        XnCallbackHandle new_user_handle;
        user_generator.RegisterUserCallbacks(CBNewUser, NULL, NULL, new_user_handle);
        user_generator.GetSkeletonCap().SetSkeletonProfile(XN_SKEL_PROFILE_ALL);//设定使用所有关节（共15个）
        //设置骨骼校正完成的回调函数
        XnCallbackHandle calibration_complete;
        user_generator.GetSkeletonCap().RegisterToCalibrationComplete(CBCalibrationComplete, NULL, calibration_complete);
        return true;
    }

    bool Start() {
        status = context.StartGeneratingAll();
        if(CheckError("Start generating error!")) {
            return false;
        }
        return true;
    }

    bool UpdateData() {
        status = context.WaitNoneUpdateAll();
        if(CheckError("Update date error!")) {
            return false;
        }
        //获取数据
        image_generator.GetMetaData(image_metadata);
        depth_generator.GetMetaData(depth_metadata);

        return true;
    }
    //得到色彩图像的node
    ImageGenerator& getImageGenerator() {
        return image_generator;
    }
    //得到深度图像的node
    DepthGenerator& getDepthGenerator() {
        return depth_generator;
    }
    //得到人体的node
    UserGenerator& getUserGenerator() {
        return user_generator;
    }
    //得到手势姿势node
    GestureGenerator& getGestureGenerator() {
        return gesture_generator;
    }

public:
    DepthMetaData depth_metadata;
    ImageMetaData image_metadata;
//    static std::map<XnUserID, vector<XnPoint3D>> hands_track_points;

private:
    //该函数返回真代表出现了错误，返回假代表正确
    bool CheckError(const char* error) {
        if(status != XN_STATUS_OK ) {
            //QMessageBox::critical(NULL, error, xnGetStatusString(status));
            cerr << error << ": " << xnGetStatusString( status ) << endl;
            return true;
        }
        return false;
    }
    //手势某个动作已经完成检测的回调函数
    static void XN_CALLBACK_TYPE  CBGestureRecognized(xn::GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pIDPosition,
                                                      const XnPoint3D *pEndPosition, void *pCookie) {
   //     COpenNI *openni = (COpenNI*)pCookie;
    //    openni->hands_generator.StartTracking(*pIDPosition);
        hands_generator.StartTracking(*pIDPosition);
    }
    //手势开始检测的回调函数
    static void XN_CALLBACK_TYPE CBGestureProgress(xn::GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pPosition,
                                                   XnFloat fProgress, void *pCookie) {
   //     COpenNI *openni = (COpenNI*)pCookie;
   //     openni->hands_generator.StartTracking(*pPosition);
        hands_generator.StartTracking(*pPosition);
    }
    //手部开始建立的回调函数
    static void XN_CALLBACK_TYPE HandCreate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition,
                                            XnFloat fTime, void* pCookie) {
   //     COpenNI *openni = (COpenNI*)pCookie;
        XnPoint3D project_pos;
        depth_generator.ConvertRealWorldToProjective(1, pPosition, &project_pos);
 //       openni->hand_point = project_pos;   //返回手部所在点的位置
        hand_point = project_pos;
        pair<XnUserID, vector<XnPoint3D>> hand_track_point(xUID, vector<XnPoint3D>());
        hand_track_point.second.push_back(project_pos);
        hands_track_points.insert(hand_track_point);
    }
    //手部开始更新的回调函数
    static void XN_CALLBACK_TYPE HandUpdate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition, XnFloat fTime,
                                            void* pCookie) {
   //     COpenNI *openni = (COpenNI*)pCookie;
        XnPoint3D project_pos;
        depth_generator.ConvertRealWorldToProjective(1, pPosition, &project_pos);
     //   openni->hand_point = project_pos;   //返回手部所在点的位置
        hand_point = project_pos;
        hands_track_points.find(xUID)->second.push_back(project_pos);
    }
    //销毁手部的回调函数
    static void XN_CALLBACK_TYPE HandDestroy(HandsGenerator& rHands, XnUserID xUID, XnFloat fTime,
                                              void* pCookie) {
  //      COpenNI *openni = (COpenNI*)pCookie;
        //openni->hand_point.clear();   //返回手部所在点的位置
        hands_track_points.erase(hands_track_points.find(xUID));
    }
    //有人进入视野时的回调函数
    static void XN_CALLBACK_TYPE CBNewUser(UserGenerator &generator, XnUserID user, void *p_cookie) {
        //得到skeleton的capability,并调用RequestCalibration函数设置对新检测到的人进行骨骼校正
        generator.GetSkeletonCap().RequestCalibration(user, true);
    }
    //完成骨骼校正的回调函数
    static void XN_CALLBACK_TYPE CBCalibrationComplete(SkeletonCapability &skeleton,
                                                       XnUserID user, XnCalibrationStatus calibration_error, void *p_cookie) {
        if(calibration_error == XN_CALIBRATION_STATUS_OK) {
            skeleton.StartTracking(user);//骨骼校正完成后就开始进行人体跟踪了
        }
        else {
            UserGenerator *p_user = (UserGenerator*)p_cookie;
            skeleton.RequestCalibration(user, true);//骨骼校正失败时重新设置对人体骨骼继续进行校正
        }
    }

private:
    XnStatus    status;
    Context     context;
    ImageGenerator  image_generator;
//    DepthGenerator depth_generator;
    UserGenerator user_generator;
    GestureGenerator gesture_generator;
//    HandsGenerator  hands_generator;
//    map<XnUserID, vector<XnPoint3D>> hands_track_points;
    XnMapOutputMode xmode;

public:
  // static XnPoint3D hand_point;
};

#endif

#include "SkeletonSensor.h"

// openCV
#include <opencv/highgui.h>
#include <opencv/cv.h>
using namespace cv;

#include <iostream>
using namespace std;

// globals
SkeletonSensor* sensor;

const unsigned int XRES = 640;
const unsigned int YRES = 480;

const float DEPTH_SCALE_FACTOR = 255./4096.;

// defines the value about which thresholding occurs
const unsigned int BIN_THRESH_OFFSET = 5;

// defines the value about witch the region of interest is extracted
const unsigned int ROI_OFFSET = 70;

// median blur factor
const unsigned int MEDIAN_BLUR_K = 5;

// grasping threshold
const double GRASPING_THRESH = 0.9;

// colors
const Scalar COLOR_BLUE        = Scalar(240,40,0);
const Scalar COLOR_DARK_GREEN  = Scalar(0, 128, 0);
const Scalar COLOR_LIGHT_GREEN = Scalar(0,255,0);
const Scalar COLOR_YELLOW      = Scalar(0,128,200);
const Scalar COLOR_RED         = Scalar(0,0,255);

// returns true if the hand is near the sensor area
bool handApproachingDisplayPerimeter(float x, float y)
{
    return (x > (XRES - ROI_OFFSET)) || (x < (ROI_OFFSET)) ||
           (y > (YRES - ROI_OFFSET)) || (y < (ROI_OFFSET));
}

// conversion from cvConvexityDefect
struct ConvexityDefect
{
    Point start;
    Point end;
    Point depth_point;
    float depth;
};

// Thanks to Jose Manuel Cabrera for part of this C++ wrapper function
//Convexity為凸的意思，Defect為缺陷的意思，hull為殼的意思
//貌似這個函數在opencv中已經被實現了
void findConvexityDefects(vector<Point>& contour, vector<int>& hull, vector<ConvexityDefect>& convexDefects)
{
    if(hull.size() > 0 && contour.size() > 0)
    {
        CvSeq* contourPoints;
        CvSeq* defects;
        CvMemStorage* storage;
        CvMemStorage* strDefects;
        CvMemStorage* contourStr;
        CvConvexityDefect *defectArray = 0;

        strDefects = cvCreateMemStorage();
        defects = cvCreateSeq( CV_SEQ_KIND_GENERIC|CV_32SC2, sizeof(CvSeq),sizeof(CvPoint), strDefects );

        //We transform our vector<Point> into a CvSeq* object of CvPoint.
        contourStr = cvCreateMemStorage();
        contourPoints = cvCreateSeq(CV_SEQ_KIND_GENERIC|CV_32SC2, sizeof(CvSeq), sizeof(CvPoint), contourStr);
        for(int i = 0; i < (int)contour.size(); i++) {
            CvPoint cp = {contour[i].x,  contour[i].y};
            cvSeqPush(contourPoints, &cp);
        }

        //Now, we do the same thing with the hull index
        int count = (int) hull.size();
        //int hullK[count];
        int* hullK = (int*) malloc(count*sizeof(int));
        for(int i = 0; i < count; i++) { hullK[i] = hull.at(i); }
        CvMat hullMat = cvMat(1, count, CV_32SC1, hullK);

        // calculate convexity defects
        storage = cvCreateMemStorage(0);
        defects = cvConvexityDefects(contourPoints, &hullMat, storage);
        defectArray = (CvConvexityDefect*)malloc(sizeof(CvConvexityDefect)*defects->total);
        cvCvtSeqToArray(defects, defectArray, CV_WHOLE_SEQ);
        //printf("DefectArray %i %i\n",defectArray->end->x, defectArray->end->y);

        //We store defects points in the convexDefects parameter.
        for(int i = 0; i<defects->total; i++){
            ConvexityDefect def;
            def.start       = Point(defectArray[i].start->x, defectArray[i].start->y);
            def.end         = Point(defectArray[i].end->x, defectArray[i].end->y);
            def.depth_point = Point(defectArray[i].depth_point->x, defectArray[i].depth_point->y);
            def.depth       = defectArray[i].depth;
            convexDefects.push_back(def);
        }

    // release memory
    cvReleaseMemStorage(&contourStr);
    cvReleaseMemStorage(&strDefects);
    cvReleaseMemStorage(&storage);

    }
}

int main(int argc, char** argv)
{

    // initialize the kinect
    sensor = new SkeletonSensor();
    sensor->initialize();
    sensor->setPointModeToProjective();

    Mat depthRaw(YRES, XRES, CV_16UC1);
    Mat depthShow(YRES, XRES, CV_8UC1);
    Mat handDebug;

    // this vector holds the displayed images of the hands
    vector<Mat> debugFrames;

    // rectangle used to extract hand regions from depth map
    Rect roi;
    roi.width  = ROI_OFFSET*2;
    roi.height = ROI_OFFSET*2;

    namedWindow("depthFrame", CV_WINDOW_AUTOSIZE);
    namedWindow("leftHandFrame", CV_WINDOW_AUTOSIZE);
    namedWindow("rightHandFrame", CV_WINDOW_AUTOSIZE);

    int key = 0;
    while(key != 27 && key != 'q')
    {

        sensor->waitForDeviceUpdateOnUser();

        // update 16 bit depth matrix
        //參數3後面乘以2是因為kinect獲得的深度數據是1個像素2字節的
        memcpy(depthRaw.data, sensor->getDepthData(), XRES*YRES*2);
        //轉換成8位深度圖
        depthRaw.convertTo(depthShow, CV_8U, DEPTH_SCALE_FACTOR);

        for(int handI = 0; handI < 2; handI++)
        {

            int handDepth;
            if(sensor->getNumTrackedUsers() > 0)
            {
                //Skeleton是包含15個人體骨骼節點的結構體
                Skeleton skel =  sensor->getSkeleton(sensor->getUID(0));
                //struct SkeletonPoint
                //{
                //   float x, y, z, confidence;
                //};
                SkeletonPoint hand;

                if( handI == 0)
                    hand = skel.leftHand;//hand中保存左手點的座標
                else
                    hand = skel.rightHand;//hand中保存有手點的座標
                if(hand.confidence == 1.0)//手部的置信度为1
                {
                    handDepth = hand.z * (DEPTH_SCALE_FACTOR);//轉換為8bit后的深度值
                    //handApproachingDisplayPerimeter返回為真是說明，手的位置已經越界
                    if(!handApproachingDisplayPerimeter(hand.x, hand.y))
                    {
                        roi.x = hand.x - ROI_OFFSET;    //截取出感興趣的區域roi，其區域大小由經驗值來設定
                        roi.y = hand.y - ROI_OFFSET;
                    }
                }
            }
            else
                handDepth = -1;

            // extract hand from image
            Mat handCpy(depthShow, roi);    //handCpy只是與depthShow共用數據內存而已
            Mat handMat = handCpy.clone();    //真正的擁有自己的內存區域

            // binary threshold
            if(handDepth != -1)
                //BIN_THRESH_OFFSET == 5;
                //手部的閾值化，檢測到手部后，根據手部前後的深度信息來提取手的輪廓，此時，handMat就是0和1的矩陣了
                handMat = (handMat > (handDepth - BIN_THRESH_OFFSET)) & (handMat < (handDepth + BIN_THRESH_OFFSET));

            // last pre-filtering step, apply median blur
            medianBlur(handMat, handMat, MEDIAN_BLUR_K);

            // create debug image of thresholded hand and cvt to RGB so hints show in color
            handDebug = handMat.clone();
            debugFrames.push_back(handDebug);
            //CV_GRAY2RGB表示3个通道的值是一样的
            cvtColor(debugFrames[handI], debugFrames[handI], CV_GRAY2RGB);

            std::vector< std::vector<Point> > contours;
            //提取全部轮廓信息到contours，轮廓信息采用水平，垂直对角线的末断点存储。
            findContours(handMat, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);

            //下面就是画多边形和点
            if (contours.size()) {
                for (int i = 0; i < contours.size(); i++) {
                    vector<Point> contour = contours[i];
                    //将vector转换成Mat型，此时的Mat还是列向量，只不过是2个通道的列向量而已
                    Mat contourMat = Mat(contour);
                    //返回轮廓的面积
                    double cArea = contourArea(contourMat);

                    if(cArea > 2000) // likely the hand
                    {
                        //找到轮廓的中心点
                        Scalar center = mean(contourMat);
                        Point centerPoint = Point(center.val[0], center.val[1]);

                        // approximate the contour by a simple curve
                        vector<Point> approxCurve;
                        //求出轮廓的封闭的曲线，保存在approxCurve，轮廓和封闭曲线直接的最大距离为10
                        approxPolyDP(contourMat, approxCurve, 10, true);

                        vector< vector<Point> > debugContourV;
                        debugContourV.push_back(approxCurve);
                        //在参数1中画出轮廓参数2，参数2必须是轮廓的集合，所以参数2是
                        //vector< vector<Point> >类型
                        //深绿色代表近似多边形
                        drawContours(debugFrames[handI], debugContourV, 0, COLOR_DARK_GREEN, 3);

                        vector<int> hull;
                        //找出近似曲线的凸包集合，集合hull中存储的是轮廓中凸包点的下标
                        convexHull(Mat(approxCurve), hull, false, false);

                        // draw the hull points
                        for(int j = 0; j < hull.size(); j++)
                        {
                            int index = hull[j];
                            //凸顶点用黄色表示
                            circle(debugFrames[handI], approxCurve[index], 3, COLOR_YELLOW, 2);
                        }

                        // find convexity defects
                        vector<ConvexityDefect> convexDefects;
                        findConvexityDefects(approxCurve, hull, convexDefects);
                        printf("Number of defects: %d.\n", (int) convexDefects.size());

                        for(int j = 0; j < convexDefects.size(); j++)
                        {
                            //缺陷点用蓝色表示
                            circle(debugFrames[handI], convexDefects[j].depth_point, 3, COLOR_BLUE, 2);

                        }

                        // assemble point set of convex hull
                        //将凸包集以点的坐标形式保存下来
                        vector<Point> hullPoints;
                        for(int k = 0; k < hull.size(); k++)
                        {
                            int curveIndex = hull[k];
                            Point p = approxCurve[curveIndex];
                            hullPoints.push_back(p);
                        }

                        // area of hull and curve
                        double hullArea  = contourArea(Mat(hullPoints));
                        double curveArea = contourArea(Mat(approxCurve));
                        double handRatio = curveArea/hullArea;

                        // hand is grasping
                        //GRASPING_THRESH == 0.9
                        if(handRatio > GRASPING_THRESH)
                            //握拳表示绿色
                            circle(debugFrames[handI], centerPoint, 5, COLOR_LIGHT_GREEN, 5);
                        else
                            //一般情况下手张开其中心点是显示红色
                            circle(debugFrames[handI], centerPoint, 5, COLOR_RED, 5);
                    }
                } // contour conditional
            } // hands loop
        }

        imshow("depthFrame", depthShow);

        //debugFrames只保存2帧图像
        if(debugFrames.size() >= 2 )
        {
            //长和宽的尺寸都扩大3倍
            resize(debugFrames[0], debugFrames[0], Size(), 3, 3);
            resize(debugFrames[1], debugFrames[1], Size(), 3, 3);
            imshow("leftHandFrame",  debugFrames[0]);
            imshow("rightHandFrame",  debugFrames[1]);
            debugFrames.clear();
        }

        key = waitKey(10);

    }

    delete sensor;

    return 0;
}

#ifndef SKELETON_SENSOR_H
#define SKELETON_SENSOR_H

#include <XnCppWrapper.h>
#include <vector>

// A 3D point with the confidence of the point's location. confidence_ > 0.5 is good
struct SkeletonPoint
{
    float x, y, z, confidence;
};

struct Skeleton
{
    SkeletonPoint head;
    SkeletonPoint neck;
    SkeletonPoint rightShoulder;
    SkeletonPoint leftShoulder;
    SkeletonPoint rightElbow;
    SkeletonPoint leftElbow;
    SkeletonPoint rightHand;
    SkeletonPoint leftHand;
    SkeletonPoint rightHip;
    SkeletonPoint leftHip;
    SkeletonPoint rightKnee;
    SkeletonPoint leftKnee;
    SkeletonPoint rightFoot;
    SkeletonPoint leftFoot;
    SkeletonPoint torso;

};

// SkeletonSensor: A wrapper for OpenNI Skeleton tracking devices
//
// Requires the OpenNI + NITE framework installation and the device driver
// Tracks users within the device FOV, and assists in collection of user joints data
class SkeletonSensor
{
    public:
        SkeletonSensor();
        ~SkeletonSensor();

        // set up the device resolution and data generators
        int initialize();

        // non-blocking wait for new data on the device
        void waitForDeviceUpdateOnUser();

        // update vector of tracked users
        void updateTrackedUsers();

        // return true if UID is among the tracked users
        bool isTracking(const unsigned int uid);

        // returns skeleton of specified user
        Skeleton getSkeleton(const unsigned int uid);

        // returns vector of skeletons for all users
        std::vector<Skeleton> getSkeletons();

        // get number of tracked users
        unsigned int getNumTrackedUsers();

        // map tracked user index to UID
        unsigned int getUID(const unsigned int index);

        // change point mode
        void setPointModeToProjective();
        void setPointModeToReal();

        // get depth and image data
        const XnDepthPixel* getDepthData();
        const XnDepthPixel* getWritableDepthData(){};
        const XnUInt8* getImageData();
        const XnLabel*     getLabels();

    private:
        xn::Context context_;
        xn::DepthGenerator depthG_;
        xn::UserGenerator userG_;
        xn::ImageGenerator imageG_;

        std::vector<unsigned int> trackedUsers_;

        // current list of hands
        //std::list<XnPoint3D> handCursors;

        bool pointModeProjective_;

        // on user detection and calibration, call specified functions
        int setCalibrationPoseCallbacks();

        // joint to point conversion, considers point mode
        void convertXnJointsToPoints(XnSkeletonJointPosition* const j, SkeletonPoint* const p, unsigned int numPoints);

        // callback functions for user and skeleton calibration events
        static void XN_CALLBACK_TYPE newUserCallback(xn::UserGenerator& generator, XnUserID nId, void* pCookie);
        static void XN_CALLBACK_TYPE lostUserCallback(xn::UserGenerator& generator, XnUserID nId, void* pCookie);
        static void XN_CALLBACK_TYPE calibrationStartCallback(xn::SkeletonCapability& capability, XnUserID nId, void* pCookie);
        static void XN_CALLBACK_TYPE calibrationCompleteCallback(xn::SkeletonCapability& capability, XnUserID nId, XnCalibrationStatus eStatus, void* pCookie);
        static void XN_CALLBACK_TYPE poseDetectedCallback(xn::PoseDetectionCapability& capability, const XnChar* strPose, XnUserID nId, void* pCookie);
};

#endif

#include "SkeletonSensor.h"
#include "log.h"

inline int CHECK_RC(const unsigned int rc, const char* const description)
{
    if(rc != XN_STATUS_OK)
    {
        put_flog(LOG_ERROR, "%s failed: %s", description, xnGetStatusString(rc));
        return -1;
    }

    return 0;
}

SkeletonSensor::SkeletonSensor()
{
    pointModeProjective_ = false;
}

SkeletonSensor::~SkeletonSensor()
{
    context_.Shutdown();
}

int SkeletonSensor::initialize()
{
    context_.Init();

    XnStatus rc = XN_STATUS_OK;

    // create depth and user generators
    rc = depthG_.Create(context_);

    if(CHECK_RC(rc, "Create depth generator") == -1)
        return -1;

    rc = userG_.Create(context_);

    if(CHECK_RC(rc, "Create user generator") == -1)
        return -1;

    rc = imageG_.Create(context_);

     if(CHECK_RC(rc, "Create image generator") == -1)
        return -1;

    XnMapOutputMode mapMode;
    depthG_.GetMapOutputMode(mapMode);

    // for now, make output map VGA resolution at 30 FPS
    mapMode.nXRes = XN_VGA_X_RES;
    mapMode.nYRes = XN_VGA_Y_RES;
    mapMode.nFPS  = 30;

    depthG_.SetMapOutputMode(mapMode);
    imageG_.SetMapOutputMode(mapMode);

    // turn on device mirroring
    if(depthG_.IsCapabilitySupported("Mirror") == true)
    {
        rc = depthG_.GetMirrorCap().SetMirror(true);
        CHECK_RC(rc, "Setting Image Mirroring on depthG");
    }

    // turn on device mirroring
    if(imageG_.IsCapabilitySupported("Mirror") == true)
    {
        rc = imageG_.GetMirrorCap().SetMirror(true);
        CHECK_RC(rc, "Setting Image Mirroring on imageG");
    }

    // make sure the user points are reported from the POV of the depth generator
    userG_.GetAlternativeViewPointCap().SetViewPoint(depthG_);
    depthG_.GetAlternativeViewPointCap().SetViewPoint(imageG_);

    // set smoothing factor
    userG_.GetSkeletonCap().SetSmoothing(0.9);

    // start data streams
    context_.StartGeneratingAll();

    // setup callbacks
    setCalibrationPoseCallbacks();

    return 0;
}

void SkeletonSensor::waitForDeviceUpdateOnUser()
{
    context_.WaitOneUpdateAll(userG_);
    updateTrackedUsers();
}

void SkeletonSensor::updateTrackedUsers()
{
    XnUserID users[64];
    XnUInt16 nUsers = userG_.GetNumberOfUsers();

    trackedUsers_.clear();

    userG_.GetUsers(users, nUsers);

    for(int i = 0; i < nUsers; i++)
    {
        if(userG_.GetSkeletonCap().IsTracking(users[i]))
        {
            trackedUsers_.push_back(users[i]);
        }
    }
}

bool SkeletonSensor::isTracking(const unsigned int uid)
{
    return userG_.GetSkeletonCap().IsTracking(uid);
}

Skeleton SkeletonSensor::getSkeleton(const unsigned int uid)
{
    Skeleton result;

    // not tracking user
    if(!userG_.GetSkeletonCap().IsTracking(uid))
        return result;

    // Array of available joints
    const unsigned int nJoints = 15;
    XnSkeletonJoint joints[nJoints] = 
    {   XN_SKEL_HEAD,
        XN_SKEL_NECK,
        XN_SKEL_RIGHT_SHOULDER,
        XN_SKEL_LEFT_SHOULDER,
        XN_SKEL_RIGHT_ELBOW,
        XN_SKEL_LEFT_ELBOW,
        XN_SKEL_RIGHT_HAND,
        XN_SKEL_LEFT_HAND,
        XN_SKEL_RIGHT_HIP,
        XN_SKEL_LEFT_HIP,
        XN_SKEL_RIGHT_KNEE,
        XN_SKEL_LEFT_KNEE,
        XN_SKEL_RIGHT_FOOT,
        XN_SKEL_LEFT_FOOT,
        XN_SKEL_TORSO 
    };

    // holds the joint position components
    XnSkeletonJointPosition positions[nJoints];

    for (unsigned int i = 0; i < nJoints; i++)
    {
        userG_.GetSkeletonCap().GetSkeletonJointPosition(uid, joints[i], *(positions+i));
    }

    SkeletonPoint points[15];
    convertXnJointsToPoints(positions, points, nJoints);

    result.head              = points[0];
    result.neck              = points[1];
    result.rightShoulder     = points[2];
    result.leftShoulder      = points[3];
    result.rightElbow        = points[4];
    result.leftElbow         = points[5];
    result.rightHand         = points[6];
    result.leftHand          = points[7];
    result.rightHip          = points[8];
    result.leftHip           = points[9];
    result.rightKnee         = points[10];
    result.leftKnee          = points[11];
    result.rightFoot         = points[12];
    result.leftFoot          = points[13];
    result.torso             = points[14];

    return result;
}

std::vector<Skeleton> SkeletonSensor::getSkeletons()
{
    std::vector<Skeleton> skeletons;

    for(unsigned int i = 0; i < getNumTrackedUsers(); i++)
    {
        Skeleton s = getSkeleton(trackedUsers_[i]);
        skeletons.push_back(s);
    }

    return skeletons;
}

unsigned int SkeletonSensor::getNumTrackedUsers()
{
    return trackedUsers_.size();
}

unsigned int SkeletonSensor::getUID(const unsigned int index)
{
    return trackedUsers_[index];
}

void SkeletonSensor::setPointModeToProjective()
{
    pointModeProjective_ = true;
}

void SkeletonSensor::setPointModeToReal()
{
    pointModeProjective_ = false;
}

const XnDepthPixel* SkeletonSensor::getDepthData()
{
    return depthG_.GetDepthMap();
}

const XnUInt8* SkeletonSensor::getImageData()
{
    return imageG_.GetImageMap();
}

const XnLabel* SkeletonSensor::getLabels()
{
    xn::SceneMetaData sceneMD;

    userG_.GetUserPixels(0, sceneMD);

    return sceneMD.Data();
}

int SkeletonSensor::setCalibrationPoseCallbacks()
{
    XnCallbackHandle hUserCallbacks, hCalibrationStart, hCalibrationComplete;

    userG_.RegisterUserCallbacks(newUserCallback, lostUserCallback, this, hUserCallbacks);
    userG_.GetSkeletonCap().RegisterToCalibrationStart(calibrationStartCallback, this, hCalibrationStart);
    userG_.GetSkeletonCap().RegisterToCalibrationComplete(calibrationCompleteCallback, this, hCalibrationComplete);

    // turn on tracking of all joints
    userG_.GetSkeletonCap().SetSkeletonProfile(XN_SKEL_PROFILE_ALL);

    return 0;
}

void SkeletonSensor::convertXnJointsToPoints(XnSkeletonJointPosition* const joints, SkeletonPoint* const points, unsigned int numPoints)
{
    XnPoint3D xpt;

    for(unsigned int i = 0; i < numPoints; i++)
    {
        xpt = joints[i].position;

        if(pointModeProjective_)
            depthG_.ConvertRealWorldToProjective(1, &xpt, &xpt);

        points[i].confidence = joints[i].fConfidence;
        points[i].x = xpt.X;
        points[i].y = xpt.Y;
        points[i].z = xpt.Z;
    }
}

void XN_CALLBACK_TYPE SkeletonSensor::newUserCallback(xn::UserGenerator& generator, XnUserID nId, void* pCookie)
{
    put_flog(LOG_DEBUG, "New user %d, auto-calibrating", nId);

    SkeletonSensor* sensor = (SkeletonSensor*) pCookie;
    sensor->userG_.GetSkeletonCap().RequestCalibration(nId, true);
}

void XN_CALLBACK_TYPE SkeletonSensor::lostUserCallback(xn::UserGenerator& generator, XnUserID nId, void* pCookie)
{
    put_flog(LOG_DEBUG, "Lost user %d", nId);
}

void XN_CALLBACK_TYPE SkeletonSensor::calibrationStartCallback(xn::SkeletonCapability& capability, XnUserID nId, void* pCookie)
{
    put_flog(LOG_DEBUG, "Calibration started for user %d", nId);
}

void XN_CALLBACK_TYPE SkeletonSensor::calibrationCompleteCallback(xn::SkeletonCapability& capability, XnUserID nId, XnCalibrationStatus eStatus, void* pCookie)
{
    SkeletonSensor* sensor = (SkeletonSensor*) pCookie;

    if(eStatus == XN_CALIBRATION_STATUS_OK)
    {
        put_flog(LOG_DEBUG, "Calibration completed: start tracking user %d", nId);

        sensor->userG_.GetSkeletonCap().StartTracking(nId);
    }
    else
    {
        put_flog(LOG_DEBUG, "Calibration failed for user %d", nId);

        sensor->userG_.GetSkeletonCap().RequestCalibration(nId, true);
    }
}

void XN_CALLBACK_TYPE SkeletonSensor::poseDetectedCallback(xn::PoseDetectionCapability& capability, const XnChar* strPose, XnUserID nId, void* pCookie)
{
    put_flog(LOG_DEBUG, "Pose detected for user %d", nId);

    SkeletonSensor* sensor = (SkeletonSensor*) pCookie;

    sensor->userG_.GetPoseDetectionCap().StopPoseDetection(nId);
    sensor->userG_.GetSkeletonCap().RequestCalibration(nId, true);
}

#ifndef COPENNI_CLASS
#define COPENNI_CLASS

#include <XnCppWrapper.h>
#include <QtGui/QtGui>
#include <iostream>
#include <map>

using namespace xn;
using namespace std;

static DepthGenerator  depth_generator;
static HandsGenerator  hands_generator;
static std::map<XnUserID, vector<XnPoint3D>> hands_track_points;

class COpenNI
{
public:
    ~COpenNI() {
        context.Release();//释放空间
    }
    bool Initial() {
        //初始化
        status = context.Init();
        if(CheckError("Context initial failed!")) {
            return false;
        }
        context.SetGlobalMirror(true);//设置镜像
        xmode.nXRes = 640;
        xmode.nYRes = 480;
        xmode.nFPS = 30;
        //产生颜色node
        status = image_generator.Create(context);
        if(CheckError("Create image generator  error!")) {
            return false;
        }
        //设置颜色图片输出模式
        status = image_generator.SetMapOutputMode(xmode);
        if(CheckError("SetMapOutputMdoe error!")) {
            return false;
        }
        //产生深度node
        status = depth_generator.Create(context);
        if(CheckError("Create depth generator  error!")) {
            return false;
        }
        //设置深度图片输出模式
        status = depth_generator.SetMapOutputMode(xmode);
        if(CheckError("SetMapOutputMdoe error!")) {
            return false;
        }
        //产生手势node
        status = gesture_generator.Create(context);
        if(CheckError("Create gesture generator error!")) {
            return false;
        }
        /*添加手势识别的种类*/
        gesture_generator.AddGesture("Wave", NULL);
        gesture_generator.AddGesture("click", NULL);
        gesture_generator.AddGesture("RaiseHand", NULL);
        gesture_generator.AddGesture("MovingHand", NULL);
        //产生手部的node
        status = hands_generator.Create(context);
        if(CheckError("Create hand generaotr error!")) {
            return false;
        }
        //产生人体node
        status = user_generator.Create(context);
        if(CheckError("Create gesturen generator error!")) {
            return false;
        }
        //视角校正
        status = depth_generator.GetAlternativeViewPointCap().SetViewPoint(image_generator);
        if(CheckError("Can't set the alternative view point on depth generator!")) {
            return false;
        }
        //设置与手势有关的回调函数
        XnCallbackHandle gesture_cb;
        gesture_generator.RegisterGestureCallbacks(CBGestureRecognized, CBGestureProgress, NULL, gesture_cb);
        //设置于手部有关的回调函数
        XnCallbackHandle hands_cb;
        hands_generator.RegisterHandCallbacks(HandCreate, HandUpdate, HandDestroy, NULL, hands_cb);
        //设置有人进入视野的回调函数
        XnCallbackHandle new_user_handle;
        user_generator.RegisterUserCallbacks(CBNewUser, NULL, NULL, new_user_handle);
        user_generator.GetSkeletonCap().SetSkeletonProfile(XN_SKEL_PROFILE_ALL);//设定使用所有关节（共15个）
        //设置骨骼校正完成的回调函数
        XnCallbackHandle calibration_complete;
        user_generator.GetSkeletonCap().RegisterToCalibrationComplete(CBCalibrationComplete, NULL, calibration_complete);
        return true;
    }

    bool Start() {
        status = context.StartGeneratingAll();
        if(CheckError("Start generating error!")) {
            return false;
        }
        return true;
    }

    bool UpdateData() {
        status = context.WaitNoneUpdateAll();
        if(CheckError("Update date error!")) {
            return false;
        }
        //获取数据
        image_generator.GetMetaData(image_metadata);
        depth_generator.GetMetaData(depth_metadata);

        return true;
    }
    //得到色彩图像的node
    ImageGenerator& getImageGenerator() {
        return image_generator;
    }
    //得到深度图像的node
    DepthGenerator& getDepthGenerator() {
        return depth_generator;
    }
    //得到人体的node
    UserGenerator& getUserGenerator() {
        return user_generator;
    }
    //得到手势姿势node
    GestureGenerator& getGestureGenerator() {
        return gesture_generator;
    }

public:
    DepthMetaData depth_metadata;
    ImageMetaData image_metadata;
//    static std::map<XnUserID, vector<XnPoint3D>> hands_track_points;

private:
    //该函数返回真代表出现了错误，返回假代表正确
    bool CheckError(const char* error) {
        if(status != XN_STATUS_OK ) {
            QMessageBox::critical(NULL, error, xnGetStatusString(status));
            cerr << error << ": " << xnGetStatusString( status ) << endl;
            return true;
        }
        return false;
    }
    //手势某个动作已经完成检测的回调函数
    static void XN_CALLBACK_TYPE  CBGestureRecognized(xn::GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pIDPosition,
                                                      const XnPoint3D *pEndPosition, void *pCookie) {
        hands_generator.StartTracking(*pIDPosition);
    }
    //手势开始检测的回调函数
    static void XN_CALLBACK_TYPE CBGestureProgress(xn::GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pPosition,
                                                   XnFloat fProgress, void *pCookie) {
        hands_generator.StartTracking(*pPosition);
    }
    //手部开始建立的回调函数
    static void XN_CALLBACK_TYPE HandCreate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition,
                                            XnFloat fTime, void* pCookie) {
        XnPoint3D project_pos;
        depth_generator.ConvertRealWorldToProjective(1, pPosition, &project_pos);
        pair<XnUserID, vector<XnPoint3D>> hand_track_point(xUID, vector<XnPoint3D>());
        hand_track_point.second.push_back(project_pos);
        hands_track_points.insert(hand_track_point);
    }
    //手部开始更新的回调函数
    static void XN_CALLBACK_TYPE HandUpdate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition, XnFloat fTime,
                                            void* pCookie) {
        XnPoint3D project_pos;
        depth_generator.ConvertRealWorldToProjective(1, pPosition, &project_pos);
        hands_track_points.find(xUID)->second.push_back(project_pos);
    }
    //销毁手部的回调函数
    static void XN_CALLBACK_TYPE HandDestroy(HandsGenerator& rHands, XnUserID xUID, XnFloat fTime,
                                              void* pCookie) {
        hands_track_points.erase(hands_track_points.find(xUID));
    }
    //有人进入视野时的回调函数
    static void XN_CALLBACK_TYPE CBNewUser(UserGenerator &generator, XnUserID user, void *p_cookie) {
        //得到skeleton的capability,并调用RequestCalibration函数设置对新检测到的人进行骨骼校正
        generator.GetSkeletonCap().RequestCalibration(user, true);
    }
    //完成骨骼校正的回调函数
    static void XN_CALLBACK_TYPE CBCalibrationComplete(SkeletonCapability &skeleton,
                                                       XnUserID user, XnCalibrationStatus calibration_error, void *p_cookie) {
        if(calibration_error == XN_CALIBRATION_STATUS_OK) {
            skeleton.StartTracking(user);//骨骼校正完成后就开始进行人体跟踪了
        }
        else {
            UserGenerator *p_user = (UserGenerator*)p_cookie;
            skeleton.RequestCalibration(user, true);//骨骼校正失败时重新设置对人体骨骼继续进行校正
        }
    }

private:
    XnStatus    status;
    Context     context;
    ImageGenerator  image_generator;
    UserGenerator user_generator;
    GestureGenerator gesture_generator;
    XnMapOutputMode xmode;
};

#endif

#include <QtGui>
#include <QDebug>
#include <XnCppWrapper.h>
#include "copenni.cpp"  //要包含cpp文件，不能直接包含类
#include <iostream>
#include <QPen>
#include <array>

using namespace std;

class CKinectReader: public QObject
{
public:
    //构造函数,用构造函数中的变量给类的私有成员赋值
    CKinectReader(COpenNI &openni, QGraphicsScene &scene) : openni(openni), scene(scene) {
        test = 0.0;
        {   //设置画笔的颜色
            pen_array[0].setWidth(3);
            pen_array[1].setColor(QColor::fromRgb( 255, 0, 0, 128 ));

            pen_array[1].setWidth( 3 );
            pen_array[1].setColor( QColor::fromRgb( 0, 255, 0, 128 ) );

            pen_array[2].setWidth( 3 );
            pen_array[2].setColor( QColor::fromRgb( 0, 0, 255, 128 ) );

            pen_array[3].setWidth( 3 );
            pen_array[3].setColor( QColor::fromRgb( 255, 0, 255, 128 ) );

            pen_array[4].setWidth( 3 );
            pen_array[4].setColor( QColor::fromRgb( 255, 255, 0, 128 ) );

            pen_array[5].setWidth( 3 );
            pen_array[5].setColor( QColor::fromRgb( 0, 255, 255, 128 ) );
        }
    }
    ~CKinectReader() {
        scene.removeItem(image_item);
        scene.removeItem(depth_item);
        delete [] p_depth_argb;
    }
    bool Start(int interval = 33) {
        openni.Start();//因为在调用CKinectReader这个类的之前会初始化好的,所以这里直接调用Start了
        image_item = scene.addPixmap(QPixmap());
        image_item->setZValue(1);
        depth_item = scene.addPixmap(QPixmap());
        depth_item->setZValue(2);
        openni.UpdateData();
        p_depth_argb = new uchar[4*openni.depth_metadata.XRes()*openni.depth_metadata.YRes()];
        startTimer(interval);//这里是继承QObject类，因此可以调用该函数
        return true;
    }
    float test ;
private:
    COpenNI &openni;    //定义引用同时没有初始化,因为在构造函数的时候用冒号来初始化
    QGraphicsScene &scene;
    QGraphicsPixmapItem *image_item;
    QGraphicsPixmapItem *depth_item;
    uchar *p_depth_argb;
    array<QPen, 6> pen_array;

private:
    void timerEvent(QTimerEvent *) {

        openni.UpdateData();
        //这里使用const，是因为右边的函数返回的值就是const类型的
        const XnDepthPixel *p_depth_pixpel = openni.depth_metadata.Data();
        unsigned int size = openni.depth_metadata.XRes()*openni.depth_metadata.YRes();
        QImage draw_depth_image;
        //找深度最大值点
        XnDepthPixel max_depth = *p_depth_pixpel;
        for(unsigned int i = 1; i < size; ++i)
            if(p_depth_pixpel[i] > max_depth )
                max_depth = p_depth_pixpel[i];
        test = max_depth;

        //将深度图像格式归一化到0~255
        int idx = 0;
        for(unsigned int i = 1; i < size; ++i) {
            //一定要使用1.0f相乘，转换成float类型，否则该工程的结果会有错误,因为这个要么是0，要么是1，0的概率要大很多
            float fscale = 1.0f*(*p_depth_pixpel)/max_depth;
            if((*p_depth_pixpel) != 0) {
                p_depth_argb[idx++] = 255*(1-fscale);    //蓝色分量
                p_depth_argb[idx++] = 0; //绿色分量
                p_depth_argb[idx++] = 255*fscale;   //红色分量，越远越红
                p_depth_argb[idx++] = 255*(1-fscale); //距离越近，越不透明
            }
            else {
                p_depth_argb[idx++] = 0;
                p_depth_argb[idx++] = 0;
                p_depth_argb[idx++] = 0;
                p_depth_argb[idx++] = 255;
            }
            ++p_depth_pixpel;//此处的++p_depth_pixpel和p_depth_pixpel++是一样的
        }
        draw_depth_image = QImage(p_depth_argb, openni.depth_metadata.XRes(), openni.depth_metadata.YRes()
                                 , QImage::Format_ARGB32);
        //该句隐含的调用了begin()方法
        QPainter painter(&draw_depth_image);
        {
            for(auto itUser = hands_track_points.cbegin(); itUser != hands_track_points.cend(); ++itUser) {
                painter.setPen(pen_array[itUser->first % pen_array.size()]);//设置画笔的颜色，按照一定的顺序循环不同的颜色
                const vector<XnPoint3D> &points = itUser->second;
                for(vector<XnPoint3D>::size_type i = 1; i < points.size(); ++i)
                    painter.drawLine(points[i-1].X, points[i-1].Y, points[i].X, points[i].Y);//画出轨迹线
            }
        }
        painter.end();//绘图结束
        //往item中设置图像色彩数据
        image_item->setPixmap(QPixmap::fromImage(
                              QImage(openni.image_metadata.Data(), openni.image_metadata.XRes(), openni.image_metadata.YRes(),
                              QImage::Format_RGB888)));
//        //往item中设置深度数据
//        depth_item->setPixmap(QPixmap::fromImage(
//                              QImage(p_depth_argb, openni.depth_metadata.XRes(), openni.depth_metadata.YRes()
//                              , QImage::Format_ARGB32)));

        depth_item->setPixmap(QPixmap::fromImage(draw_depth_image));
    }
};

#include <QtGui/QtGui>
#include "copenni.cpp"
#include "ckinectreader.cpp"

int main( int argc, char **argv )
{
    COpenNI openni;
    if(!openni.Initial())//初始化返回1表示初始化成功
        return 1;
    QApplication app(argc, argv);

    QGraphicsScene scene;
    QGraphicsView view;
    view.setScene(&scene);
    view.resize(650, 540);
    view.show();

    CKinectReader kinect_reader(openni, scene);
    kinect_reader.Start();//启动，读取数据

    return app.exec();
}