kinect+openni2+nite2+opencv2.4手势跟踪

#include "stdafx.h"
#include <afxwin.h>
#include <array>
#include <iostream>
#include <map>
#include <vector>// OpenCV 头文件
#include "opencv2/opencv.hpp"
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>// NiTE 头文件
#include <OpenNI.h>
#include <NiTE.h>using namespace std;
using namespace openni;
using namespace nite;
const unsigned int roi_offset=70;
const unsigned int BIN_THRESH_OFFSET =5;
const unsigned int MEDIAN_BLUR_K = 5;
const double GRASPING_THRESH = 0.9;const cv:: Scalar COLOR_BLUE        =cv::Scalar(240,40,0);
const cv::Scalar COLOR_DARK_GREEN  = cv::Scalar(0, 128, 0);
const cv::Scalar COLOR_LIGHT_GREEN =cv:: Scalar(0,255,0);
const cv::Scalar COLOR_YELLOW      =cv:: Scalar(0,128,200);
const cv::Scalar COLOR_RED         = cv::Scalar(0,0,255);
float handDepth ;
float handflag=5;
float opencvframe=3;
struct ConvexityDefect
{cv::Point start;cv::Point end;cv::Point depth_point;float depth;
};
int main( int argc, char **argv )
{// 初始化OpenNIOpenNI::initialize();// 打开Kinect设备Device  mDevice;mDevice.open( ANY_DEVICE );// 创建深度数据流VideoStream mDepthStream;mDepthStream.create( mDevice, SENSOR_DEPTH );// 设置VideoMode模式VideoMode mDepthMode;mDepthMode.setResolution( 640, 480 );mDepthMode.setFps( 30 );mDepthMode.setPixelFormat( PIXEL_FORMAT_DEPTH_1_MM );mDepthStream.setVideoMode(mDepthMode);// 同样的设置彩色数据流VideoStream mColorStream;mColorStream.create( mDevice, SENSOR_COLOR );// 设置VideoMode模式VideoMode mColorMode;mColorMode.setResolution( 640, 480 );mColorMode.setFps( 30 );mColorMode.setPixelFormat( PIXEL_FORMAT_RGB888 );mColorStream.setVideoMode( mColorMode);// 设置深度图像映射到彩色图像mDevice.setImageRegistrationMode( IMAGE_REGISTRATION_DEPTH_TO_COLOR );// 初始化 NiTENiTE::initialize();// 创建HandTracker跟踪器HandTracker mHandTracker;if( mHandTracker.create() != nite::STATUS_OK ){cerr << "Can't create user tracker" << endl;return -1;}// 设定手势探测（GESTURE_WAVE、GESTURE_CLICK和GESTURE_HAND_RAISE）mHandTracker.startGestureDetection( GESTURE_WAVE );mHandTracker.startGestureDetection( GESTURE_CLICK );//mHandTracker.startGestureDetection( GESTURE_HAND_RAISE );//mHandTracker.setSmoothingFactor(0.1f);// 创建深度图像显示cv::namedWindow("Depth Image", CV_WINDOW_AUTOSIZE);// 创建彩色图像显示cv::namedWindow( "Color Image",  CV_WINDOW_AUTOSIZE );// 保存点坐标map< HandId,vector<cv::Point2f> > mapHandData;map< HandId,float > mapHanddepth;vector<cv::Point2f> vWaveList;vector<cv::Point2f> vClickList;cv::Point2f ptSize( 3, 3 );array<cv::Scalar,8>    aHandColor;aHandColor[0] = cv::Scalar( 255, 0, 0 );aHandColor[1] = cv::Scalar( 0, 255, 0 );aHandColor[2] = cv::Scalar( 0, 0, 255 );aHandColor[3] = cv::Scalar( 255, 255, 0 );aHandColor[4] = cv::Scalar( 255, 0, 255 );aHandColor[5] = cv::Scalar( 0, 255, 255 );aHandColor[6] = cv::Scalar( 255, 255, 255 );aHandColor[7] = cv::Scalar( 0, 0, 0 );// 环境初始化后，开始获取深度数据流和彩色数据流mDepthStream.start();mColorStream.start();// 获得最大深度值int iMaxDepth = mDepthStream.getMaxPixelValue();// startwhile( true ){/* POINT pt;GetCursorPos(&pt);cerr<<pt.x<<" "<<pt.y<<endl;*/// 创建OpenCV：：Mat，用于显示彩色数据图像cv::Mat cImageBGR;// 读取彩色数据帧信息流VideoFrameRef mColorFrame;mColorStream.readFrame( &mColorFrame );// 将彩色数据流转换为OpenCV格式，记得格式是：CV_8UC3（含R\G\B）const cv::Mat mImageRGB( mColorFrame.getHeight(), mColorFrame.getWidth(),CV_8UC3, (void*)mColorFrame.getData() );// RGB ==> BGRcv::cvtColor( mImageRGB, cImageBGR, CV_RGB2BGR );// 获取手FrameHandTrackerFrameRef mHandFrame;if( mHandTracker.readFrame( &mHandFrame ) == nite::STATUS_OK ){openni::VideoFrameRef mDepthFrame = mHandFrame.getDepthFrame();// 将深度数据转换成OpenCV格式const cv::Mat mImageDepth( mDepthFrame.getHeight(), mDepthFrame.getWidth(), CV_16UC1, (void*)mDepthFrame.getData() );// 为了让深度图像显示的更加明显一些，将CV_16UC1 ==> CV_8U格式cv::Mat mScaledDepth, mImageBGR;mImageDepth.convertTo( mScaledDepth, CV_8U, 255.0 / iMaxDepth );// 将灰度图转换成BGR格式，为了画出点的颜色坐标和轨迹cv::cvtColor( mScaledDepth, mImageBGR, CV_GRAY2BGR );// 检测手势const nite::Array<GestureData>& aGestures = mHandFrame.getGestures();for( int i = 0; i < aGestures.getSize(); ++ i ){const GestureData& rGesture = aGestures[i];const Point3f& rPos = rGesture.getCurrentPosition();cv::Point2f rPos2D;mHandTracker.convertHandCoordinatesToDepth( rPos.x, rPos.y, rPos.z, &rPos2D.x, &rPos2D.y );HandId mHandID;if( mHandTracker.startHandTracking( rPos, &mHandID ) != nite::STATUS_OK )cerr << "Can't track hand" << endl;}// 得到手心坐标const nite::Array<HandData>& aHands = mHandFrame.getHands();for( int i = 0; i < aHands.getSize(); ++ i ){const HandData& rHand = aHands[i];HandId uID = rHand.getId();if( rHand.isNew() ){mapHandData.insert( make_pair( uID, vector<cv::Point2f>() ) );mapHanddepth.insert(make_pair(uID,float()));}if( rHand.isTracking() ){// 将手心坐标映射到彩色图像和深度图像中const Point3f& rPos = rHand.getPosition();cv::Point2f rPos2D;mHandTracker.convertHandCoordinatesToDepth( rPos.x, rPos.y, rPos.z, &rPos2D.x, &rPos2D.y );handDepth = rPos.z * 255/iMaxDepth;cv::Point2f aPoint=rPos2D;cv::circle( cImageBGR, aPoint, 3, cv::Scalar( 0, 0, 255 ), 4 );cv::circle( mScaledDepth, aPoint, 3, cv::Scalar(0, 0, 255), 4);// 在彩色图像中画出手的轮廓边cv::Point2f ctlPoint, ctrPoint, cdlPoint, cdrPoint;ctlPoint.x = aPoint.x - 100;ctlPoint.y = aPoint.y - 100;ctrPoint.x = aPoint.x - 100;ctrPoint.y = aPoint.y + 100;cdlPoint.x = aPoint.x + 100;cdlPoint.y = aPoint.y - 100;cdrPoint.x = aPoint.x + 100;cdrPoint.y = aPoint.y + 100;cv::line( cImageBGR, ctlPoint, ctrPoint, cv::Scalar( 255, 0, 0 ), 3 );cv::line( cImageBGR, ctlPoint, cdlPoint, cv::Scalar( 255, 0, 0 ), 3 );cv::line( cImageBGR, cdlPoint, cdrPoint, cv::Scalar( 255, 0, 0 ), 3 );cv::line( cImageBGR, ctrPoint, cdrPoint, cv::Scalar( 255, 0, 0 ), 3 );// 在深度图像中画出手的轮廓边cv::Point2f mtlPoint, mtrPoint, mdlPoint, mdrPoint;mtlPoint.x = aPoint.x - 100;mtlPoint.y = aPoint.y - 100;mtrPoint.x = aPoint.x - 100;mtrPoint.y = aPoint.y + 100;mdlPoint.x = aPoint.x + 100;mdlPoint.y = aPoint.y - 100;mdrPoint.x = aPoint.x + 100;mdrPoint.y = aPoint.y + 100;cv::line( mScaledDepth, mtlPoint, mtrPoint, cv::Scalar( 255, 0, 0 ), 3 );cv::line( mScaledDepth, mtlPoint, mdlPoint, cv::Scalar( 255, 0, 0 ), 3 );cv::line( mScaledDepth, mdlPoint, mdrPoint, cv::Scalar( 255, 0, 0 ), 3 );cv::line( mScaledDepth, mtrPoint, mdrPoint, cv::Scalar( 255, 0, 0 ), 3 );mapHandData[uID].push_back( rPos2D );mapHanddepth[uID]=handDepth;}if( rHand.isLost() ){mapHandData.erase(uID );mapHanddepth.erase(uID);}}for( auto itHand = mapHandData.begin(); itHand != mapHandData.end(); ++ itHand ){const cv::Scalar& rColor = aHandColor[ itHand->first % aHandColor.size() ];const vector<cv::Point2f>& rPoints = itHand->second;for( int i = 1; i < rPoints.size(); ++ i ){cv::line( mImageBGR, rPoints[i-1], rPoints[i], rColor, 2 );cv::line( cImageBGR, rPoints[i-1], rPoints[i], rColor, 2 );}}cv::imshow( "Depth Image", mImageBGR );cv::imshow("Color Image", cImageBGR);mHandFrame.release();}else{cerr << "Can't get new frame" << endl;}// 按键“q”退出循环if( cv::waitKey( 1 ) == 'q' )break;}mHandTracker.destroy();mColorStream.destroy();NiTE::shutdown();OpenNI::shutdown();return 0;
}

在手的部位画出一个矩形框，模拟画线，实现效果图

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