opencv2 camshift目标跟踪详解及测试代码

本文转自：http://blog.csdn.net/gdfsg/article/details/51029370

1. CamShift思想       

       Camshift全称是"Continuously Adaptive Mean-SHIFT"，即连续自适应的MeanShift算法，是MeanShift算法的改进。CamShift的基本思想是视频图像的所有帧作MeanShift运算，并将上一帧的结果（即Search Window的中心和大小）作为下一帧MeanShift算法的Search Window的初始值，如此迭代下去。

       这个过程其实和用MeanShift做跟踪一样，可以参见我的另一篇博文“Meanshift之目标跟踪”，这里把我画的流程图搬过来。

2. cvCamShift( )详解

     CamShift号称连续自适应MeanShift，在算法理论上并没有什么区别，甚至在编程的流程上也没什么区别，他们的区别体现在程序内部

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1. int cvCamShift( const void* imgProb,        //概率图  
2.             CvRect windowIn,                    //起始跟踪区域  
3.             CvTermCriteria criteria,            //迭代终止条件  
4.             CvConnectedComp* _comp,             //可选参数，表示连通域结构体    
5.             CvBox2D* box )                      //可选参数，存储旋转矩形的坐标，包括中心，尺寸和旋转角  

int cvCamShift( const void* imgProb,        //概率图            CvRect windowIn,                    //起始跟踪区域            CvTermCriteria criteria,            //迭代终止条件            CvConnectedComp* _comp,             //可选参数，表示连通域结构体              CvBox2D* box )                      //可选参数，存储旋转矩形的坐标，包括中心，尺寸和旋转角

和MeanShift一样，返回值是迭代次数。这里比MeanShift多了一个参数box。

函数原型见 ..\OpenCV249\sources\modules\video\src\camshift.cpp

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1. CV_IMPL int  
2. cvCamShift( const void* imgProb, CvRect windowIn,  
3.             CvTermCriteria criteria,  
4.             CvConnectedComp* _comp,  
5.             CvBox2D* box )  
6. {  
7.     const int TOLERANCE = 10;  //公差=10  
8.     CvMoments moments;  
9.     double m00 = 0, m10, m01, mu20, mu11, mu02, inv_m00;  
10.     double a, b, c, xc, yc;  
11.     double rotate_a, rotate_c;  
12.     double theta = 0, square;  
13.     double cs, sn;  
14.     double length = 0, width = 0;  
15.     int itersUsed = 0;  
16.     CvConnectedComp comp;  
17.     CvMat  cur_win, stub, *mat = (CvMat*)imgProb;  
18.   
19.     CV_FUNCNAME( "cvCamShift" );  
20.   
21.     comp.rect = windowIn;  
22.   
23.     __BEGIN__;  
24.   
25.     CV_CALL( mat = cvGetMat( mat, &stub ));  
26.   
27.     //调用cvMeanShift函数  
28.     CV_CALL( itersUsed = cvMeanShift( mat, windowIn, criteria, &comp ));  
29.     windowIn = comp.rect;  
30.       
31.     //-------------下面的程序是和MeanShift( )的区别所在------------  
32.     //区别1：对边界情况进行处理,  
33.     //CamShift()中将windowIn沿x和y方向拉大了2个TOLERANCE，并且确保windowIn不越界。Meanshift无此操作  
34.     windowIn.x -= TOLERANCE;  
35.     if( windowIn.x < 0 )  
36.         windowIn.x = 0;  
37.   
38.     windowIn.y -= TOLERANCE;  
39.     if( windowIn.y < 0 )  
40.         windowIn.y = 0;  
41.   
42.     windowIn.width += 2 * TOLERANCE;  
43.     if( windowIn.x + windowIn.width > mat->width )  
44.         windowIn.width = mat->width - windowIn.x;  
45.   
46.     windowIn.height += 2 * TOLERANCE;  
47.     if( windowIn.y + windowIn.height > mat->height )  
48.         windowIn.height = mat->height - windowIn.y;  
49.   
50.     CV_CALL( cvGetSubRect( mat, &cur_win, windowIn ));//在mat中提取windowIn区域  
51.   
52.     /* Calculating moments in new center mass */  
53.     //计算新中心处的颜色统计矩  
54.     CV_CALL( cvMoments( &cur_win, &moments ));  
55.   
56.     //区别2：计算并保存了目标旋转的结果，meanshit()并未考虑旋转  
57.     m00 = moments.m00;      //0阶空间矩  
58.     m10 = moments.m10;      //水平1阶  
59.     m01 = moments.m01;      //垂直1阶  
60.     mu11 = moments.mu11;    //水平垂直2阶中心距  
61.     mu20 = moments.mu20;    //水平2阶  
62.     mu02 = moments.mu02;    //垂直2阶  
63.   
64.     //目标矩形的质量太小了就退出  
65.     if( fabs(m00) < DBL_EPSILON )//系统预定于的值，DBL_EPSILON=2.2204460492503131e-016  
66.         EXIT;  
67.   
68.     //质量的倒数，只是为了下面计算方便，可以把除法表示成乘法  
69.     inv_m00 = 1. / m00;  
70.     xc = cvRound( m10 * inv_m00 + windowIn.x );  
71.     yc = cvRound( m01 * inv_m00 + windowIn.y );  //(xc,yc)是重心相对于图像的坐标想  
72.     a = mu20 * inv_m00;  
73.     b = mu11 * inv_m00;  
74.     c = mu02 * inv_m00;  
75.   
76.     /* Calculating width & height */  
77.     square = sqrt( 4 * b * b + (a - c) * (a - c) );  
78.   
79.     /* Calculating orientation */  
80.     //计算目标主轴方向角度  
81.     theta = atan2( 2 * b, a - c + square );   //theta是与x轴的夹角  
82.   
83.     /* Calculating width & length of figure */  
84.     cs = cos( theta );  
85.     sn = sin( theta );  
86.   
87.     rotate_a = cs * cs * mu20 + 2 * cs * sn * mu11 + sn * sn * mu02;  
88.     rotate_c = sn * sn * mu20 - 2 * cs * sn * mu11 + cs * cs * mu02;  
89.     //下次搜索窗口的长宽，注意不是width和height  
90.     length = sqrt( rotate_a * inv_m00 ) * 4;  
91.     width = sqrt( rotate_c * inv_m00 ) * 4;  
92.   
93.     /*根据length和width的大小对length、width、theta进行调整*/  
94.     if( length < width )  
95.     {  
96.         double t;  
97.           
98.         CV_SWAP( length, width, t );  
99.         CV_SWAP( cs, sn, t );  
100.         theta = CV_PI*0.5 - theta;  
101.     }  
102.   
103.     /* 结果保存在comp中 */  
104.     if( _comp || box )  
105.     {  
106.         int t0, t1;  
107.         int _xc = cvRound( xc );  
108.         int _yc = cvRound( yc );  
109.   
110.         t0 = cvRound( fabs( length * cs ));  
111.         t1 = cvRound( fabs( width * sn ));  
112.   
113.         t0 = MAX( t0, t1 ) + 2;  
114.         comp.rect.width = MIN( t0, (mat->width - _xc) * 2 );  
115.   
116.         t0 = cvRound( fabs( length * sn ));  
117.         t1 = cvRound( fabs( width * cs ));  
118.   
119.         t0 = MAX( t0, t1 ) + 2;  
120.         comp.rect.height = MIN( t0, (mat->height - _yc) * 2 );  
121.   
122.         comp.rect.x = MAX( 0, _xc - comp.rect.width / 2 );  
123.         comp.rect.y = MAX( 0, _yc - comp.rect.height / 2 );  
124.   
125.         comp.rect.width = MIN( mat->width - comp.rect.x, comp.rect.width );  
126.         comp.rect.height = MIN( mat->height - comp.rect.y, comp.rect.height );  
127.         comp.area = (float) m00;  
128.     }  
129.   
130.     __END__;  
131.   
132.     if( _comp )  
133.         *_comp = comp;  
134.       
135.     if( box )    //box里存的是目标的相关参数  
136.     {  
137.         box->size.height = (float)length;  
138.         box->size.width = (float)width;  
139.         box->angle = (float)(theta*180./CV_PI);  
140.         box->center = cvPoint2D32f( comp.rect.x + comp.rect.width*0.5f,  
141.                                     comp.rect.y + comp.rect.height*0.5f);  
142.     }  
143.   
144.     return itersUsed;   //返回迭代次数  
145. }  

CV_IMPL intcvCamShift( const void* imgProb, CvRect windowIn,            CvTermCriteria criteria,            CvConnectedComp* _comp,            CvBox2D* box ){    const int TOLERANCE = 10;  //公差=10    CvMoments moments;    double m00 = 0, m10, m01, mu20, mu11, mu02, inv_m00;    double a, b, c, xc, yc;    double rotate_a, rotate_c;    double theta = 0, square;    double cs, sn;    double length = 0, width = 0;    int itersUsed = 0;    CvConnectedComp comp;    CvMat  cur_win, stub, *mat = (CvMat*)imgProb;    CV_FUNCNAME( "cvCamShift" );    comp.rect = windowIn;    __BEGIN__;    CV_CALL( mat = cvGetMat( mat, &stub ));    //调用cvMeanShift函数    CV_CALL( itersUsed = cvMeanShift( mat, windowIn, criteria, &comp ));    windowIn = comp.rect;//-------------下面的程序是和MeanShift( )的区别所在------------//区别1：对边界情况进行处理,//CamShift()中将windowIn沿x和y方向拉大了2个TOLERANCE，并且确保windowIn不越界。Meanshift无此操作    windowIn.x -= TOLERANCE;    if( windowIn.x < 0 )        windowIn.x = 0;    windowIn.y -= TOLERANCE;    if( windowIn.y < 0 )        windowIn.y = 0;    windowIn.width += 2 * TOLERANCE;    if( windowIn.x + windowIn.width > mat->width )        windowIn.width = mat->width - windowIn.x;    windowIn.height += 2 * TOLERANCE;    if( windowIn.y + windowIn.height > mat->height )        windowIn.height = mat->height - windowIn.y;    CV_CALL( cvGetSubRect( mat, &cur_win, windowIn ));//在mat中提取windowIn区域    /* Calculating moments in new center mass */    //计算新中心处的颜色统计矩    CV_CALL( cvMoments( &cur_win, &moments ));//区别2：计算并保存了目标旋转的结果，meanshit()并未考虑旋转    m00 = moments.m00;//0阶空间矩    m10 = moments.m10;//水平1阶    m01 = moments.m01;//垂直1阶    mu11 = moments.mu11;//水平垂直2阶中心距    mu20 = moments.mu20;//水平2阶    mu02 = moments.mu02;//垂直2阶    //目标矩形的质量太小了就退出    if( fabs(m00) < DBL_EPSILON )//系统预定于的值，DBL_EPSILON=2.2204460492503131e-016        EXIT;    //质量的倒数，只是为了下面计算方便，可以把除法表示成乘法    inv_m00 = 1. / m00;    xc = cvRound( m10 * inv_m00 + windowIn.x );    yc = cvRound( m01 * inv_m00 + windowIn.y );  //(xc,yc)是重心相对于图像的坐标想    a = mu20 * inv_m00;    b = mu11 * inv_m00;    c = mu02 * inv_m00;    /* Calculating width & height */    square = sqrt( 4 * b * b + (a - c) * (a - c) );    /* Calculating orientation */    //计算目标主轴方向角度    theta = atan2( 2 * b, a - c + square );   //theta是与x轴的夹角    /* Calculating width & length of figure */    cs = cos( theta );    sn = sin( theta );    rotate_a = cs * cs * mu20 + 2 * cs * sn * mu11 + sn * sn * mu02;    rotate_c = sn * sn * mu20 - 2 * cs * sn * mu11 + cs * cs * mu02;    //下次搜索窗口的长宽，注意不是width和height    length = sqrt( rotate_a * inv_m00 ) * 4;    width = sqrt( rotate_c * inv_m00 ) * 4;    /*根据length和width的大小对length、width、theta进行调整*/    if( length < width )    {        double t;                CV_SWAP( length, width, t );        CV_SWAP( cs, sn, t );        theta = CV_PI*0.5 - theta;    }    /* 结果保存在comp中 */    if( _comp || box )    {        int t0, t1;        int _xc = cvRound( xc );        int _yc = cvRound( yc );        t0 = cvRound( fabs( length * cs ));        t1 = cvRound( fabs( width * sn ));        t0 = MAX( t0, t1 ) + 2;        comp.rect.width = MIN( t0, (mat->width - _xc) * 2 );        t0 = cvRound( fabs( length * sn ));        t1 = cvRound( fabs( width * cs ));        t0 = MAX( t0, t1 ) + 2;        comp.rect.height = MIN( t0, (mat->height - _yc) * 2 );        comp.rect.x = MAX( 0, _xc - comp.rect.width / 2 );        comp.rect.y = MAX( 0, _yc - comp.rect.height / 2 );        comp.rect.width = MIN( mat->width - comp.rect.x, comp.rect.width );        comp.rect.height = MIN( mat->height - comp.rect.y, comp.rect.height );        comp.area = (float) m00;    }    __END__;    if( _comp )        *_comp = comp;        if( box )    //box里存的是目标的相关参数    {        box->size.height = (float)length;        box->size.width = (float)width;        box->angle = (float)(theta*180./CV_PI);        box->center = cvPoint2D32f( comp.rect.x + comp.rect.width*0.5f,                                    comp.rect.y + comp.rect.height*0.5f);    }    return itersUsed;   //返回迭代次数}

将CamShift( )和MeanShift( )对比，可以看到这些差别

1、CamShift( )中将cur_win沿x和y方向拉大了2个TOLERANCE，MeanShift( )无此操作

2、CamShift( )考虑了目标发生旋转的情况，并给出了旋转角，MeanShift( )无此操作

3.实验代码及结果

来看看OpenCV自带的demo，原程序见D:\Programs_L\OpenCV249\sources\samples\cpp\camshiftdemo.cpp

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1. #include "opencv2/video/tracking.hpp"  
2. #include "opencv2/imgproc/imgproc.hpp"  
3. #include "opencv2/highgui/highgui.hpp"  
4.   
5. #include <iostream>  
6. #include <ctype.h>  
7.   
8. using namespace cv;  
9. using namespace std;  
10.   
11. Mat image;  
12.   
13. bool backprojMode = false;  
14. bool selectObject = false;  
15. int trackObject = 0;  
16. bool showHist = true;  
17. Point origin;  
18. Rect selection;  
19. int vmin = 10, vmax = 256, smin = 30;  
20.   
21. static void onMouse( int event, int x, int y, int, void* )  
22. {  
23.     if( selectObject )  
24.     {  
25.         selection.x = MIN(x, origin.x);  
26.         selection.y = MIN(y, origin.y);  
27.         selection.width = std::abs(x - origin.x);  
28.         selection.height = std::abs(y - origin.y);  
29.   
30.         selection &= Rect(0, 0, image.cols, image.rows);  
31.     }  
32.   
33.     switch( event )  
34.     {  
35.     case CV_EVENT_LBUTTONDOWN:  
36.         origin = Point(x,y);  
37.         selection = Rect(x,y,0,0);  
38.         selectObject = true;  
39.         break;  
40.     case CV_EVENT_LBUTTONUP:  
41.         selectObject = false;  
42.         if( selection.width > 0 && selection.height > 0 )  
43.             trackObject = -1;  
44.         break;  
45.     }  
46. }  
47.   
48. static void help()  
49. {  
50.     cout << "\nThis is a demo that shows mean-shift based tracking\n"  
51.             "You select a color objects such as your face and it tracks it.\n"  
52.             "This reads from video camera (0 by default, or the camera number the user enters\n"  
53.             "Usage: \n"  
54.             "   ./camshiftdemo [camera number]\n";  
55.   
56.     cout << "\n\nHot keys: \n"  
57.             "\tESC - quit the program\n"  
58.             "\tc - stop the tracking\n"  
59.             "\tb - switch to/from backprojection view\n"  
60.             "\th - show/hide object histogram\n"  
61.             "\tp - pause video\n"  
62.             "To initialize tracking, select the object with mouse\n";  
63. }  
64.   
65. const char* keys =  
66. {  
67.     "{1|  | 0 | camera number}"  
68. };  
69.   
70. int main( int argc, const char** argv )  
71. {  
72.     help();  
73.   
74.     VideoCapture cap;  
75.     Rect trackWindow;  
76.     int hsize = 16;  
77.     float hranges[] = {0,180};  
78.     const float* phranges = hranges;  
79.     CommandLineParser parser(argc, argv, keys);  
80.     int camNum = parser.get<int>("1");  
81.   
82.     cap.open(camNum);  
83.   
84.     if( !cap.isOpened() )  
85.     {  
86.         help();  
87.         cout << "***Could not initialize capturing...***\n";  
88.         cout << "Current parameter's value: \n";  
89.         parser.printParams();  
90.         return -1;  
91.     }  
92.   
93.     namedWindow( "Histogram", 0 );  
94.     namedWindow( "CamShift Demo", 0 );  
95.     setMouseCallback( "CamShift Demo", onMouse, 0 );  
96.     createTrackbar( "Vmin", "CamShift Demo", &vmin, 256, 0 );  
97.     createTrackbar( "Vmax", "CamShift Demo", &vmax, 256, 0 );  
98.     createTrackbar( "Smin", "CamShift Demo", &smin, 256, 0 );  
99.   
100.     Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;  
101.     bool paused = false;  
102.   
103.     for(;;)  
104.     {  
105.         if( !paused )  
106.         {  
107.             cap >> frame;  
108.             if( frame.empty() )  
109.                 break;  
110.         }  
111.   
112.         frame.copyTo(image);  
113.   
114.         if( !paused )  
115.         {  
116.             cvtColor(image, hsv, COLOR_BGR2HSV);  
117.   
118.             if( trackObject )  
119.             {  
120.                 int _vmin = vmin, _vmax = vmax;  
121.   
122.                 inRange(hsv, Scalar(0, smin, MIN(_vmin,_vmax)),  
123.                         Scalar(180, 256, MAX(_vmin, _vmax)), mask);  //mask初始化  
124.                 int ch[] = {0, 0};  
125.                 hue.create(hsv.size(), hsv.depth());  
126.                 mixChannels(&hsv, 1, &hue, 1, ch, 1);  //提取h通道  
127.   
128.                 if( trackObject < 0 )  
129.                 {  
130.                     Mat roi(hue, selection), maskroi(mask, selection);  
131.                     calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);   //计算目标直方图  
132.                     normalize(hist, hist, 0, 255, CV_MINMAX);  
133.   
134.                     trackWindow = selection;  
135.                     trackObject = 1;  
136.   
137.                     histimg = Scalar::all(0);  
138.                     int binW = histimg.cols / hsize;  
139.                     Mat buf(1, hsize, CV_8UC3);  
140.                     for( int i = 0; i < hsize; i++ )  
141.                         buf.at<Vec3b>(i) = Vec3b(saturate_cast<uchar>(i*180./hsize), 255, 255);  
142.                     cvtColor(buf, buf, CV_HSV2BGR);  
143.   
144.                     for( int i = 0; i < hsize; i++ )  
145.                     {  
146.                         int val = saturate_cast<int>(hist.at<float>(i)*histimg.rows/255);  
147.                         rectangle( histimg, Point(i*binW,histimg.rows),  
148.                                    Point((i+1)*binW,histimg.rows - val),  
149.                                    Scalar(buf.at<Vec3b>(i)), -1, 8 );  
150.                     }  
151.                 }  
152.   
153.                 calcBackProject(&hue, 1, 0, hist, backproj, &phranges);  
154.                 backproj &= mask;  
155.                 RotatedRect trackBox = CamShift(backproj, trackWindow,  
156.                                     TermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ));  
157.                 if( trackWindow.area() <= 1 )  
158.                 {  
159.                     int cols = backproj.cols, rows = backproj.rows, r = (MIN(cols, rows) + 5)/6;  
160.                     trackWindow = Rect(trackWindow.x - r, trackWindow.y - r,  
161.                                        trackWindow.x + r, trackWindow.y + r) &  
162.                                   Rect(0, 0, cols, rows);  
163.                 }  
164.   
165.                 if( backprojMode )  
166.                     cvtColor( backproj, image, COLOR_GRAY2BGR );  
167.                 ellipse( image, trackBox, Scalar(0,0,255), 3, CV_AA );  
168.                 //rectangle( image, trackBox, Scalar(0,0,255), 3, CV_AA );  
169.             }  
170.         }  
171.         else if( trackObject < 0 )  
172.             paused = false;  
173.   
174.         if( selectObject && selection.width > 0 && selection.height > 0 )  
175.         {  
176.             Mat roi(image, selection);  
177.             bitwise_not(roi, roi);  
178.         }  
179.   
180.         imshow( "CamShift Demo", image );  
181.         imshow( "Histogram", histimg );  
182.   
183.         char c = (char)waitKey(10);  
184.         if( c == 27 )  
185.             break;  
186.         switch(c)  
187.         {  
188.         case 'b':  
189.             backprojMode = !backprojMode;  
190.             break;  
191.         case 'c':  
192.             trackObject = 0;  
193.             histimg = Scalar::all(0);  
194.             break;  
195.         case 'h':  
196.             showHist = !showHist;  
197.             if( !showHist )  
198.                 destroyWindow( "Histogram" );  
199.             else  
200.                 namedWindow( "Histogram", 1 );  
201.             break;  
202.         case 'p':  
203.             paused = !paused;  
204.             break;  
205.         default:  
206.             ;  
207.         }  
208.     }  
209.   
210.     return 0;  
211. }  

#include "opencv2/video/tracking.hpp"#include "opencv2/imgproc/imgproc.hpp"#include "opencv2/highgui/highgui.hpp"#include <iostream>#include <ctype.h>using namespace cv;using namespace std;Mat image;bool backprojMode = false;bool selectObject = false;int trackObject = 0;bool showHist = true;Point origin;Rect selection;int vmin = 10, vmax = 256, smin = 30;static void onMouse( int event, int x, int y, int, void* ){    if( selectObject )    {        selection.x = MIN(x, origin.x);        selection.y = MIN(y, origin.y);        selection.width = std::abs(x - origin.x);        selection.height = std::abs(y - origin.y);        selection &= Rect(0, 0, image.cols, image.rows);    }    switch( event )    {    case CV_EVENT_LBUTTONDOWN:        origin = Point(x,y);        selection = Rect(x,y,0,0);        selectObject = true;        break;    case CV_EVENT_LBUTTONUP:        selectObject = false;        if( selection.width > 0 && selection.height > 0 )            trackObject = -1;        break;    }}static void help(){    cout << "\nThis is a demo that shows mean-shift based tracking\n"            "You select a color objects such as your face and it tracks it.\n"            "This reads from video camera (0 by default, or the camera number the user enters\n"            "Usage: \n"            "   ./camshiftdemo [camera number]\n";    cout << "\n\nHot 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"            "\tp - pause video\n"            "To initialize tracking, select the object with mouse\n";}const char* keys ={    "{1|  | 0 | camera number}"};int main( int argc, const char** argv ){    help();    VideoCapture cap;    Rect trackWindow;    int hsize = 16;    float hranges[] = {0,180};    const float* phranges = hranges;    CommandLineParser parser(argc, argv, keys);    int camNum = parser.get<int>("1");    cap.open(camNum);    if( !cap.isOpened() )    {        help();        cout << "***Could not initialize capturing...***\n";        cout << "Current parameter's value: \n";        parser.printParams();        return -1;    }    namedWindow( "Histogram", 0 );    namedWindow( "CamShift Demo", 0 );    setMouseCallback( "CamShift Demo", onMouse, 0 );    createTrackbar( "Vmin", "CamShift Demo", &vmin, 256, 0 );    createTrackbar( "Vmax", "CamShift Demo", &vmax, 256, 0 );    createTrackbar( "Smin", "CamShift Demo", &smin, 256, 0 );    Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;    bool paused = false;    for(;;)    {        if( !paused )        {            cap >> frame;            if( frame.empty() )                break;        }        frame.copyTo(image);        if( !paused )        {            cvtColor(image, hsv, COLOR_BGR2HSV);            if( trackObject )            {                int _vmin = vmin, _vmax = vmax;                inRange(hsv, Scalar(0, smin, MIN(_vmin,_vmax)),                        Scalar(180, 256, MAX(_vmin, _vmax)), mask);  //mask初始化                int ch[] = {0, 0};                hue.create(hsv.size(), hsv.depth());                mixChannels(&hsv, 1, &hue, 1, ch, 1);  //提取h通道                if( trackObject < 0 )                {                    Mat roi(hue, selection), maskroi(mask, selection);                    calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);   //计算目标直方图                    normalize(hist, hist, 0, 255, CV_MINMAX);                    trackWindow = selection;                    trackObject = 1;                    histimg = Scalar::all(0);                    int binW = histimg.cols / hsize;                    Mat buf(1, hsize, CV_8UC3);                    for( int i = 0; i < hsize; i++ )                        buf.at<Vec3b>(i) = Vec3b(saturate_cast<uchar>(i*180./hsize), 255, 255);                    cvtColor(buf, buf, CV_HSV2BGR);                    for( int i = 0; i < hsize; i++ )                    {                        int val = saturate_cast<int>(hist.at<float>(i)*histimg.rows/255);                        rectangle( histimg, Point(i*binW,histimg.rows),                                   Point((i+1)*binW,histimg.rows - val),                                   Scalar(buf.at<Vec3b>(i)), -1, 8 );                    }                }                calcBackProject(&hue, 1, 0, hist, backproj, &phranges);                backproj &= mask;                RotatedRect trackBox = CamShift(backproj, trackWindow,                                    TermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ));                if( trackWindow.area() <= 1 )                {                    int cols = backproj.cols, rows = backproj.rows, r = (MIN(cols, rows) + 5)/6;                    trackWindow = Rect(trackWindow.x - r, trackWindow.y - r,                                       trackWindow.x + r, trackWindow.y + r) &                                  Rect(0, 0, cols, rows);                }                if( backprojMode )                    cvtColor( backproj, image, COLOR_GRAY2BGR );                ellipse( image, trackBox, Scalar(0,0,255), 3, CV_AA );//rectangle( image, trackBox, Scalar(0,0,255), 3, CV_AA );            }        }        else if( trackObject < 0 )            paused = false;        if( selectObject && selection.width > 0 && selection.height > 0 )        {            Mat roi(image, selection);            bitwise_not(roi, roi);        }        imshow( "CamShift Demo", image );        imshow( "Histogram", histimg );        char c = (char)waitKey(10);        if( c == 27 )            break;        switch(c)        {        case 'b':            backprojMode = !backprojMode;            break;        case 'c':            trackObject = 0;            histimg = Scalar::all(0);            break;        case 'h':            showHist = !showHist;            if( !showHist )                destroyWindow( "Histogram" );            else                namedWindow( "Histogram", 1 );            break;        case 'p':            paused = !paused;            break;        default:            ;        }    }    return 0;}

实验效果和之前的MeanShift差不多，图就懒得帖了。

用的时候感觉有时候甚至不如MeanShift。比如用meanshift跟踪时，手消失在人脸的位置后，meanshift会跟踪人脸，当人手再次从人脸位置出现时，会再跟踪手；而camshift被人脸干扰后，不会再跟踪手。原因未明。。。