使用Opencv中的Camshift进行视频中目标跟踪是一个不错的选择,这方面的示例很多,但是大多代码不全,或者代码存在问题,不能正常使用,这里,对很多文章进行整理后,贴出了正确可以使用的代码。
首先下载OpenCV, http://sourceforge.net/projects/opencvlibrary/
安装Opencv ,他是exe,可以直接安装。
具体安装过程见转载的一篇博文:http://blog.csdn.net/luopeiyuan1990/article/details/8775069
安装完成后,建立工程勿忘记在工程汇总添加include和lib的搜索目录,最后也要添加动态链接库如下:
使用开发环境:VS2010实测。
动态链接库
opencv_core245d.lib
opencv_core245.lib
opencv_highgui245.lib
opencv_highgui245d.lib
opencv_imgproc245.lib
opencv_imgproc245d.lib
opencv_video245.lib
opencv_video245d.lib
如果不安装错误信息的其中一条如下:
错误 1 error LNK2019: 无法解析的外部符号 "void __cdecl cv::destroyWindow(class std::basic_string<char,struct std::char_traits<char>,class std::allocator<char> > const &)" (?destroyWindow@cv@@YAXABV?$basic_string@DU?$char_traits@D@std@@V?$allocator@D@2@@std@@@Z),该符号在函数 _main 中被引用 E:\documents\visual studio 2010\Projects\Track\Track\main.obj
错误原因:库文件设置不正确
解决办法:项目->属性->连接器->输入->附加依赖项,添加程序所依赖的库文件,本程序用到opencv_core220d.lib 和opencv_highgui220d.lib(上面的动态库建议全部加上)
使用过程中还可能出现其他错误比如:
proxytrans.ax could not be loaded
本错误时Opencv1.0中的一个注册项的缺省安装造成,安装opencv1.0就可以了,地址如下:
http://www.opencv.org.cn/download/OpenCV_1.0.exe
另一个错误:
错误::“cvSetMouseCallback”: 不能将参数 2 从“void (__cdecl *)(int,int,int,int)”转换为“CvMouseCallback”
原因:函数命名不符合Opencv的命名规范如下更改即可。
//void on_mouse( int event, int x, int y, int flags )
void on_mouse(int event, int x, int y, int flags, void* param)
汇总例程的下载地址:
http://ishare.iask.sina.com.cn/f/36709094.html
一个可以参考的教程下载地址如下:
http://ishare.iask.sina.com.cn/f/9105002.html
下面贴出本例程中,使用的代码,实现了,简单的目标的跟踪:使用的是笔记本自带的摄像头,可以简单的跟踪你的脸哦,呵呵。还不是太灵敏,有待改进,本例程是结合,Opencv自带的例程以及网友的贡献代码更改,有任何问题,可以给我留言,或者联系我,方式见上。
#include "cv.h" #include "highgui.h" #include <stdio.h> #include <ctype.h> IplImage *image = 0, *hsv = 0, *hue = 0, *mask = 0, *backproject = 0, *histimg = 0; CvHistogram *hist = 0; int backproject_mode = 0; int select_object = 0; int track_object = 0; int show_hist = 1; CvPoint origin; CvRect selection; CvRect track_window; CvBox2D track_box; // tracking 返回的区域 box,带角度 CvConnectedComp track_comp; int hdims = 48; // 划分HIST的个数,越高越精确 float hranges_arr[] = {0,180}; float* hranges = hranges_arr; int vmin = 10, vmax = 256, smin = 30; //void on_mouse( int event, int x, int y, int flags ) void on_mouse(int event, int x, int y, int flags, void* param) { if( !image ) return; if( image->origin ) y = image->height - y; if( select_object ) { selection.x = MIN(x,origin.x); selection.y = MIN(y,origin.y); selection.width = selection.x + CV_IABS(x - origin.x); selection.height = selection.y + CV_IABS(y - origin.y); selection.x = MAX( selection.x, 0 ); selection.y = MAX( selection.y, 0 ); selection.width = MIN( selection.width, image->width ); selection.height = MIN( selection.height, image->height ); selection.width -= selection.x; selection.height -= selection.y; } switch( event ) { case CV_EVENT_LBUTTONDOWN: origin = cvPoint(x,y); selection = cvRect(x,y,0,0); select_object = 1; break; case CV_EVENT_LBUTTONUP: select_object = 0; if( selection.width > 0 && selection.height > 0 ) track_object = -1; #ifdef _DEBUG printf("\n # 鼠标的选择区域:"); printf("\n X = %d, Y = %d, Width = %d, Height = %d", selection.x, selection.y, selection.width, selection.height); #endif break; } } CvScalar hsv2rgb( float hue ) { int rgb[3], p, sector; static const int sector_data[][3]= {{0,2,1}, {1,2,0}, {1,0,2}, {2,0,1}, {2,1,0}, {0,1,2}}; hue *= 0.033333333333333333333333333333333f; sector = cvFloor(hue); p = cvRound(255*(hue - sector)); p ^= sector & 1 ? 255 : 0; rgb[sector_data[sector][0]] = 255; rgb[sector_data[sector][1]] = 0; rgb[sector_data[sector][2]] = p; #ifdef _DEBUG printf("\n # Convert HSV to RGB:"); printf("\n HUE = %f", hue); printf("\n R = %d, G = %d, B = %d", rgb[0],rgb[1],rgb[2]); #endif return cvScalar(rgb[2], rgb[1], rgb[0],0); } int main( int argc, char** argv ) { CvCapture* capture = 0; IplImage* frame = 0; if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0]))) capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 0 ); else if( argc == 2 ) capture = cvCaptureFromAVI( argv[1] ); if( !capture ) { fprintf(stderr,"Could not initialize capturing...\n"); return -1; } printf( "Hot keys: \n" "\tESC - quit the program\n" "\tc - stop the tracking\n" "\tb - switch to/from backprojection view\n" "\th - show/hide object histogram\n" "To initialize tracking, select the object with mouse\n" ); //cvNamedWindow( "Histogram", 1 ); cvNamedWindow( "CamShiftDemo", 1 ); cvSetMouseCallback( "CamShiftDemo", on_mouse, NULL ); // on_mouse 自定义事件 cvCreateTrackbar( "Vmin", "CamShiftDemo", &vmin, 256, 0 ); cvCreateTrackbar( "Vmax", "CamShiftDemo", &vmax, 256, 0 ); cvCreateTrackbar( "Smin", "CamShiftDemo", &smin, 256, 0 ); for(;;) { int i, bin_w, c; frame = cvQueryFrame( capture ); if( !frame ) break; if( !image ) { /* allocate all the buffers */ image = cvCreateImage( cvGetSize(frame), 8, 3 ); image->origin = frame->origin; hsv = cvCreateImage( cvGetSize(frame), 8, 3 ); hue = cvCreateImage( cvGetSize(frame), 8, 1 ); mask = cvCreateImage( cvGetSize(frame), 8, 1 ); backproject = cvCreateImage( cvGetSize(frame), 8, 1 ); hist = cvCreateHist( 1, &hdims, CV_HIST_ARRAY, &hranges, 1 ); // 计算直方图 histimg = cvCreateImage( cvSize(320,200), 8, 3 ); cvZero( histimg ); } cvCopy( frame, image, 0 ); cvCvtColor( image, hsv, CV_BGR2HSV ); // 彩色空间转换 BGR to HSV if( track_object ) { int _vmin = vmin, _vmax = vmax; cvInRangeS( hsv, cvScalar(0,smin,MIN(_vmin,_vmax),0), cvScalar(180,256,MAX(_vmin,_vmax),0), mask ); // 得到二值的MASK cvSplit( hsv, hue, 0, 0, 0 ); // 只提取 HUE 分量 if( track_object < 0 ) { float max_val = 0.f; cvSetImageROI( hue, selection ); // 得到选择区域 for ROI cvSetImageROI( mask, selection ); // 得到选择区域 for mask cvCalcHist( &hue, hist, 0, mask ); // 计算直方图 cvGetMinMaxHistValue( hist, 0, &max_val, 0, 0 ); // 只找最大值 cvConvertScale( hist->bins, hist->bins, max_val ? 255. / max_val : 0., 0 ); // 缩放 bin 到区间 [0,255] cvResetImageROI( hue ); // remove ROI cvResetImageROI( mask ); track_window = selection; track_object = 1; cvZero( histimg ); bin_w = histimg->width / hdims; // hdims: 条的个数,则 bin_w 为条的宽度 // 画直方图 for( i = 0; i < hdims; i++ ) { int val = cvRound( cvGetReal1D(hist->bins,i)*histimg->height/255 ); CvScalar color = hsv2rgb(i*180.f/hdims); cvRectangle( histimg, cvPoint(i*bin_w,histimg->height), cvPoint((i+1)*bin_w,histimg->height - val), color, -1, 8, 0 ); } } cvCalcBackProject( &hue, backproject, hist ); // 使用 back project 方法 cvAnd( backproject, mask, backproject, 0 ); // calling CAMSHIFT 算法模块 cvCamShift( backproject, track_window, cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ), &track_comp, &track_box ); track_window = track_comp.rect; if( backproject_mode ) cvCvtColor( backproject, image, CV_GRAY2BGR ); // 使用backproject灰度图像 if( image->origin ) track_box.angle = -track_box.angle; cvEllipseBox( image, track_box, CV_RGB(255,0,0), 3, CV_AA, 0 ); } if( select_object && selection.width > 0 && selection.height > 0 ) { cvSetImageROI( image, selection ); cvXorS( image, cvScalarAll(255), image, 0 ); cvResetImageROI( image ); } cvShowImage( "CamShiftDemo", image ); cvShowImage( "Histogram", histimg ); c = cvWaitKey(10); if( c == 27 ) break; // exit from for-loop switch( c ) { case 'b': backproject_mode ^= 1; break; case 'c': track_object = 0; cvZero( histimg ); break; case 'h': show_hist ^= 1; if( !show_hist ) cvDestroyWindow( "Histogram" ); else cvNamedWindow( "Histogram", 1 ); break; default: ; } } cvReleaseCapture( &capture ); cvDestroyWindow("CamShiftDemo"); return 0; }