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，
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：
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.libopencv_core245.libopencv_highgui245.libopencv_highgui245d.libopencv_imgproc245.libopencv_imgproc245d.libopencv_video245.libopencv_video245d.lib 如果不安装错误信息的其中一条如下：错误1error 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：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：
一个可以参考的教程下载地址如下：
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 _DEBUGprintf("\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);#endifbreak;}}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 _DEBUGprintf("\n # Convert HSV to RGB：");printf("\n HUE = %f", hue);printf("\n R = %d, G = %d, B = %d", rgb[0],rgb[1],rgb[2]);#endifreturn 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 HSVif( 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MASKcvSplit( 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 ROIcvSetImageROI( mask, selection ); // 得到选择区域 for maskcvCalcHist( &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 ROIcvResetImageROI( 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-loopswitch( 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" );elsecvNamedWindow( "Histogram", 1 );break;default:;}}cvReleaseCapture( &capture );cvDestroyWindow("CamShiftDemo");return 0;}
走过的路成为背后的风景，不能回头不能停留，若此刻停留，
