利用KINECT+OPENCV检测手势的演示程序

2011-4-10 增加结果图片，更新代码，将模板改为6个（0-5）

 

1，原理：读入KINECT深度数据，转换为二值图像，找到轮廓，与轮廓模板比较，找到HU矩阵最小的为匹配结果

2，基础：OPENNI, OPENCV2.2 以及http://blog.163.com/gz_ricky/blog/static/182049118201122311118325/
的例程基础上修改

3，结果：仅仅用于演示利用OPENCV+OPENNI编程，对结果精度，处理速度等没有优化，仅供参考

 

对0，1和5的比较比较准确

 

废话少说，一切都在代码中

// KinectOpenCVTest.cpp : 定义控制台应用程序的入口点。//#include "stdafx.h"#include <stdlib.h>#include <iostream>#include <string>#include <XnCppWrapper.h>#include <opencv2/opencv.hpp>//#include "opencv/cv.h"//#include "opencv/highgui.h"using namespace std;using namespace cv;#define SAMPLE_XML_PATH "../../Data/SamplesConfig.xml"//全局模板轮廓vector<vector<Point>> g_TemplateContours;//模板个数int g_handTNum = 6;void CheckOpenNIError( XnStatus eResult, string sStatus ){ if( eResult != XN_STATUS_OK ) {cerr << sStatus << " Error: " << xnGetStatusString( eResult ) << endl;return;}}//载入模板的轮廓void init_hand_template(){//int handTNum = 10;string temp = "HandTemplate/";int i = 0;for(i=0; i<g_handTNum; i++){stringstream ss;ss << i << ".bmp";string fileName = temp + ss.str(); //读入灰度图像Mat src = imread(fileName, 0);if(!src.data){printf("未找到文件: %s/n", fileName);continue;}vector<vector<Point>> contours;vector<Vec4i> hierarchy;findContours(src, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);//findContours(src, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);g_TemplateContours.push_back(contours[0]);}}//模板匹配手int hand_template_match(Mat& hand){//int handTNum = 10;int minId = -1;double minHu = 1;double hu;int method = CV_CONTOURS_MATCH_I1;//match_num = 0;for(int i=0; i<g_handTNum; i++){Mat temp(g_TemplateContours.at(i));hu = matchShapes(temp, hand, method, 0);//找到hu矩最小的模板if(hu < minHu){minHu = hu;minId = i;}//printf("%f ", hu);}//显示匹配结果int Hmatch_value = 25;//模板匹配系数if(minHu<((double)Hmatch_value)/100)return minId;elsereturn -1;}void findHand(Mat& src, Mat& dst){vector<vector<Point>> contours;vector<Vec4i> hierarchy;//找到外部轮廓//findContours(src, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);findContours(src, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE); //CV_CHAIN_APPROX_NONE);//findContours(src, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);Mat dst_r = Mat::zeros(src.rows, src.cols, CV_8UC3);dst_r.copyTo(dst);// iterate through all the top-level contours,// draw each connected component with its own random colorint idx = 0;double maxArea = 0.0;int maxId = -1;for(unsigned int i = 0; i<contours.size(); i++){Mat temp(contours.at(i));double area = fabs(contourArea(temp));if(area > maxArea){maxId = i;maxArea = area;}}//for( ; idx >= 0; idx = hierarchy[idx][0] )//{////Scalar color( rand()&255, rand()&255, rand()&255 );////drawContours(dst, contours, idx, color, CV_FILLED, 8, hierarchy );//double area = contourArea(contours.at(idx));//if(area > maxArea)//{//maxId = idx;//maxArea = area;//}//}//显示最大轮廓外形，以及最佳匹配的模板IDif(contours.size() > 0){Scalar color(0, 255, 255 );drawContours(dst, contours, maxId, color);Mat hand(contours.at(maxId));int value = hand_template_match(hand);if(value >= 0){Scalar templateColor(255, 0, 255 );drawContours(dst, g_TemplateContours, value, templateColor);printf("Match %d /r/n", value);stringstream ss;ss << "Match " << value;string text = ss.str();putText(dst, text, Point(300, 30), FONT_HERSHEY_SIMPLEX, 1.0, templateColor);}}}int HandDetect(){init_hand_template();XnStatus eResult = XN_STATUS_OK; // 1. initial valxn::DepthMetaData m_DepthMD;xn::ImageMetaData m_ImageMD;// for opencv MatMat m_depth16u( 480,640,CV_16UC1);Mat m_rgb8u( 480,640,CV_8UC3);Mat m_DepthShow( 480,640,CV_8UC1);Mat m_ImageShow( 480,640,CV_8UC3);Mat m_DepthThreshShow( 480,640,CV_8UC1);Mat m_HandShow( 480,640,CV_8UC3);//cvNamedWindow("depth");//cvNamedWindow("image");//cvNamedWindow("depthThresh");char key=0;// 2. initial context xn::Context mContext; eResult = mContext.Init(); //xn::EnumerationErrors errors;//eResult = mContext.InitFromXmlFile(SAMPLE_XML_PATH, &errors);CheckOpenNIError( eResult, "initialize context" ); //Set mirrormContext.SetGlobalMirror(!mContext.GetGlobalMirror());// 3. create depth generator xn::DepthGenerator mDepthGenerator; eResult = mDepthGenerator.Create( mContext ); CheckOpenNIError( eResult, "Create depth generator" ); // 4. create image generator xn::ImageGenerator mImageGenerator;eResult = mImageGenerator.Create( mContext ); CheckOpenNIError( eResult, "Create image generator" );// 5. set map mode XnMapOutputMode mapMode; mapMode.nXRes = 640; mapMode.nYRes = 480; mapMode.nFPS = 30; eResult = mDepthGenerator.SetMapOutputMode( mapMode ); eResult = mImageGenerator.SetMapOutputMode( mapMode ); //由于 Kinect 的深度摄像机和彩色摄像机是在不同的位置，而且镜头本身的参数也不完全相同，所以两个摄像机所取得的画面会有些微的差异//将深度摄像机的视角调整到RGB摄像机位置// 6. correct view port mDepthGenerator.GetAlternativeViewPointCap().SetViewPoint( mImageGenerator ); // 7. start generate data eResult = mContext.StartGeneratingAll(); // 8. read data eResult = mContext.WaitNoneUpdateAll(); while( (key!=27) && !(eResult = mContext.WaitNoneUpdateAll( )) ) { // 9a. get the depth map mDepthGenerator.GetMetaData(m_DepthMD);memcpy(m_depth16u.data,m_DepthMD.Data(), 640*480*2);// 9b. get the image map mImageGenerator.GetMetaData(m_ImageMD);memcpy(m_rgb8u.data,m_ImageMD.Data(),640*480*3);//将未知深度转为白色，便于在OPENCV中分析XnDepthPixel* pDepth = (XnDepthPixel*)m_depth16u.data;for (XnUInt y = 0; y < m_DepthMD.YRes(); ++y){for (XnUInt x = 0; x < m_DepthMD.XRes(); ++x, ++pDepth){if (*pDepth == 0){*pDepth = 0xFFFF;}}}//由于OpenNI获得的深度图片是16位无符号整数，而OpenCV显示的是8位的，所以要作转换。//将距离转换为灰度值（0-2550mm 转换到 0-255），例如1000毫米转换为 1000×255/2550 = 100//m_depth16u.convertTo(m_DepthShow,CV_8U, 255/2096.0);m_depth16u.convertTo(m_DepthShow,CV_8U, 255/2550.0);//可以考虑根据数据缩减图像大小到有效范围//在此对灰度图像进行处理，平滑和去噪声//medianBlur(m_DepthShow, m_DepthThreshShow, 3);//m_DepthThreshShow.copyTo(m_DepthShow);//medianBlur(m_DepthThreshShow, m_DepthShow, 3);blur(m_DepthShow, m_DepthThreshShow, Size(3, 3));//m_DepthThreshShow.copyTo(m_DepthShow);blur(m_DepthThreshShow, m_DepthShow, Size(3, 3));Mat pyrTemp( 240,320,CV_8UC1);pyrDown(m_DepthShow, pyrTemp);pyrUp(pyrTemp, m_DepthShow);//dilate(m_DepthShow, m_DepthThreshShow, Mat(), Point(-1,-1), 3);//erode(m_DepthThreshShow, m_DepthShow, Mat(), Point(-1,-1), 3);//for(int i = 0; i < m_depth16u.rows; i++)//for(int j = 0; j < m_depth16u.cols; j++)//{//if(m_depth16u.at<unsigned short>(i,j) < 1)//m_depth16u.at<unsigned short>(i,j) == 0xFFFF;////m_depth16u.at<double>(i,j)=1./(i+j+1);//}//RGB和BGR在内存对应的位置序列不同，所以也要转换。cvtColor(m_rgb8u,m_ImageShow,CV_RGB2BGR);//imshow("depth", m_DepthShow);//imshow("image", m_ImageShow);double thd_max = 0xFFFF;double thd_val = 100.0;//反转黑白图像，以便找到最大外部轮廓//threshold(m_DepthShow, m_DepthThreshShow, thd_val, thd_max, CV_THRESH_BINARY);threshold(m_DepthShow, m_DepthThreshShow, thd_val, thd_max, CV_THRESH_BINARY_INV);imshow("depthThresh", m_DepthThreshShow);findHand(m_DepthThreshShow, m_HandShow);imshow( "Hand", m_HandShow );key=cvWaitKey(20);}// 10. stop mContext.StopGeneratingAll();mContext.Shutdown(); return 0;}int _tmain(int argc, _TCHAR* argv[]){HandDetect();}