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：
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;
}