Hog+Camshift的人体跟踪

#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()
{
int number = 0;
CvCapture* capture = 0;
capture = cvCaptureFromAVI("112218.avi");


if( !capture )
    {
        fprintf(stderr,"Could not initialize capturing...\n");
        return -1;
    }


cvNamedWindow( "HogSiftDemo", 1 );


for(;;)
{
cout<<number<<endl;
number++;
IplImage* frame = 0;
        frame = cvQueryFrame( capture );
//frame = cvLoadImage("D:\\My Documents\\Visual Studio 2008\\Projects\\hogmeansift\\Debug\\crop001009.png");


if(track_object == 0)
{
r = ObjectDectd(frame,track_object,r);
if(r.x!=0)
track_object  = -1;
}
else frame = MeanSift(frame,r);


//cvRectangle(frame, r.tl(), r.br(), cv::Scalar(0,255,0), 3);
cvShowImage("HogSiftDemo", frame);
waitKey(1);


}
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 track_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 );
       // histimg = cvCreateImage( cvSize(320,200), 8, 3 );
        //cvZero( histimg );
    }


    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( backproject_mode )
            cvCvtColor( backproject, image, CV_GRAY2BGR );
        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;
r.width = track_comp.rect.height;
r.y = track_comp.rect.y;
r.height = track_comp.rect.width;
cvRectangle(image, r.tl(), r.br(), cv::Scalar(0,255,0), 3);
    }


    if( select_object && selection.width > 0 && selection.height > 0 )
    {
        cvSetImageROI( image, selection );
        cvXorS( image, cvScalarAll(255), image, 0 );
        cvResetImageROI( image );
    }
return image;
}
原文地址:https://www.cnblogs.com/polly333/p/4498446.html