Hog 和 CamShift 结合， 这个就是 非常的粗糙的 代码堆积

Hog  和  CamShift  结合效果可以

#include <fstream>#include <string>#include <cv.h>#include <highgui.h>#include <ml.h>#include <iostream>#include <fstream>#include <string>#include <vector>#include "cvaux.h"#include <iostream>#include <stdio.h>#include <string.h>#include <ctype.h>using namespace cv;using namespace std;Rect r ;int track_object = 0;Rect ObjectDectd(IplImage* frame,int object,Rect r);IplImage* MeanSift(IplImage *frame,Rect r);int main(){CvCapture* capture = 0;capture = cvCaptureFromAVI("sfe_clip.avi");if( !capture ){fprintf(stderr,"Could not initialize capturing...\n");return -1;}cvNamedWindow( "HogSiftDemo", 1 );//HogDetect  oHogDetect;for(;;){IplImage* frame = 0;frame = cvQueryFrame( capture );if(track_object == 0){r = ObjectDectd(frame,track_object,r);cvRectangle(frame, r.tl(), r.br(), cv::Scalar(255,255,0), 3);if(!cvSaveImage("mm1.jpg",frame)) printf("Could not save: %s\n", "mm1.jpg");std::cout<<"NOT Changed:"<<r.x <<"   "<<r.y<<"  "<<r.width<<"   "<<r.height<<std::endl; if(r.x!=0)track_object  = -1;r.x = r.x + 30; r.y = r.y +30;r.width = r.width / 3;//4;//6;//9; r.height = r.height / 3;//4;//6; cvRectangle(frame, r.tl(), r.br(), cv::Scalar(255,255,0), 3);if(!cvSaveImage("mm2.jpg",frame)) printf("Could not save: %s\n", "mm1.jpg");std::cout<<"Changed:"<<r.x <<"   "<<r.y<<"  "<<r.width<<"   "<<r.height<<std::endl; }else frame = MeanSift(frame,r);//cvRectangle(frame, r.tl(), r.br(), cv::Scalar(0,255,0), 3);cvShowImage("HogSiftDemo", frame);waitKey(33);}cvReleaseCapture( &capture );cvDestroyWindow("HogSiftDemo");return 0;}Rect ObjectDectd(IplImage* frame,int object,Rect r){HOGDescriptor hog;hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());Mat img;img = frame;  fflush(stdout);vector<Rect> found, found_filtered;double t = (double)getTickCount();//int can = img.channels();hog.detectMultiScale(img, found, 0, Size(8,8), Size(32,32), 1.05, 2);t = (double)getTickCount() - t;printf("tdetection time = %gms\n", t*1000./cv::getTickFrequency());size_t i, j;if(found.size()!=0){//object = 1;for( i = 0; i < found.size(); i++ ){r = found[i];for( j = 0; j < found.size(); j++ )if( j != i && (r & found[j]) == r)break;if( j == found.size() )found_filtered.push_back(r);}for( i = 0; i < found_filtered.size(); i++ ){r = found_filtered[i];r.x += cvRound(r.width*0.1);r.width = cvRound(r.width*1);r.y += cvRound(r.height*0.07);r.height = cvRound(r.height*0.8);//cvRectangle(frame, r.tl(), r.br(), cv::Scalar(0,255,0), 3);}}return r;}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 show_hist = 1;CvPoint origin;CvRect selection;CvRect track_window;CvBox2D track_box;CvConnectedComp track_comp;int hdims = 16;float hranges_arr[] = {0,180};float* hranges = hranges_arr;int vmin = 10, vmax = 256, smin = 30;int i, bin_w, c;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;return cvScalar(rgb[2], rgb[1], rgb[0],0);}IplImage* MeanSift(IplImage *frame,Rect r){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 );}cvCopy( frame, image, 0 );cvCvtColor( image, hsv, CV_BGR2HSV );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 );cvSplit( hsv, hue, 0, 0, 0 );if( track_object < 0 ){selection.height = r.height;selection.width = r.width;selection.x = r.x;selection.y = r.y;float max_val = 0.f;cvSetImageROI( hue, selection );cvSetImageROI( mask, selection );cvCalcHist( &hue, hist, 0, mask );cvGetMinMaxHistValue( hist, 0, &max_val, 0, 0 );cvConvertScale( hist->bins, hist->bins, max_val ? 255. / max_val : 0., 0 );cvResetImageROI( hue );cvResetImageROI( mask );track_window = selection;track_object = 1;}cvCalcBackProject( &hue, backproject, hist );cvAnd( backproject, mask, backproject, 0 );cvCamShift( backproject, track_window,cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),&track_comp, &track_box );track_window = track_comp.rect;if( !image->origin )track_box.angle = -track_box.angle;//cvEllipseBox( image, track_box, CV_RGB(255,0,0), 3, CV_AA, 0 );Rect r;  r.x = track_comp.rect.x - 5;r.width = track_comp.rect.height -20 ;r.y = track_comp.rect.y - 20;r.height = track_comp.rect.width +100;cvRectangle(image, r.tl(), r.br(), cv::Scalar(0,255,0), 3);}return image;}

测试视频：http://download.csdn.net/detail/sfe1012/7777977