请问谁能提供opencv实现的视频中运动行人检测与追踪的程序?
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记得给我分,急需
#include "cv.h"
#include <cxcore.h>
#include "highgui.h"
#include <time.h>
#include <math.h>
#include <ctype.h>
#include <stdio.h>
#include <string.h>
// various tracking parameters (in seconds)
const double MHI_DURATION = 0.5;
const double MAX_TIME_DELTA = 0.5;
const double MIN_TIME_DELTA = 0.05;
const int N = 3;
//
const int CONTOUR_MAX_AERA = 16;
// ring image buffer
IplImage **buf = 0;
int last = 0;
// temporary images
IplImage *mhi = 0;
// MHI: motion history image
int filter = CV_GAUSSIAN_5x5;
CvConnectedComp *cur_comp, min_comp;
CvConnectedComp comp;
CvMemStorage *storage; CvPoint pt[4];
// 参数:
// img – 输入视频帧
// dst – 检测结果
void update_mhi( IplImage* img, IplImage* dst, int diff_threshold )
{
double timestamp = clock()/100.;
// get current time in seconds
CvSize size = cvSize(img->width,img->height);
// get current frame size
int i, j, idx1, idx2;
IplImage* silh;
uchar val;
float temp;
IplImage* pyr = cvCreateImage( cvSize((size.width & -2)/2, (size.height & -2)/2), 8, 1 );
CvMemStorage *stor;
CvSeq *cont, *result, *squares;
CvSeqReader reader;
if( !mhi || mhi->width != size.width || mhi->height != size.height )
{
if( buf == 0 )
{
buf = (IplImage**)malloc(N*sizeof(buf[0]));
memset( buf, 0, N*sizeof(buf[0]));
}
for( i = 0; i < N; i++ )
{
cvReleaseImage( &buf[i] );
buf[i] = cvCreateImage( size, IPL_DEPTH_8U, 1 );
cvZero( buf[i] );
}
cvReleaseImage( &mhi );
mhi = cvCreateImage( size, IPL_DEPTH_32F, 1 );
cvZero( mhi );
// clear MHI at the beginning
}
// end of if(mhi)
cvCvtColor( img, buf[last], CV_BGR2GRAY );
// convert frame to grayscale
idx1 = last;
idx2 = (last + 1) % N;
// index of (last - (N-1))th frame
last = idx2;
// 做帧差
silh = buf[idx2];
cvAbsDiff( buf[idx1], buf[idx2], silh );
// get difference between frames
// 对差图像做二值化
cvThreshold( silh, silh, 30, 255, CV_THRESH_BINARY );
// and threshold it
cvUpdateMotionHistory( silh, mhi, timestamp, MHI_DURATION );
// update MHI
cvCvtScale( mhi, dst, 255./MHI_DURATION,
(MHI_DURATION - timestamp)*255./MHI_DURATION );
cvCvtScale( mhi, dst, 255./MHI_DURATION, 0 );
// 中值滤波,消除小的噪声
cvSmooth( dst, dst, CV_MEDIAN, 3, 0, 0, 0 );
// 向下采样,去掉噪声
cvPyrDown( dst, pyr, 7 );
cvDilate( pyr, pyr, 0, 1 );
// 做膨胀操作,消除目标的不连续空洞
cvPyrUp( pyr, dst, 7 );
//
// 下面的程序段用来找到轮廓
//
// Create dynamic structure and sequence.
stor = cvCreateMemStorage(0);
cont = cvCreateSeq(CV_SEQ_ELTYPE_POINT, sizeof(CvSeq), sizeof(CvPoint) , stor);
// 找到所有轮廓
cvFindContours( dst, stor, &cont, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0));
// 直接使用CONTOUR中的矩形来画轮廓
for(;cont;cont = cont->h_next)
{
CvRect r = ((CvContour*)cont)->rect;
if(r.height * r.width > CONTOUR_MAX_AERA) // 面积小的方形抛弃掉
{
cvRectangle( img, cvPoint(r.x,r.y),
cvPoint(r.x + r.width, r.y + r.height),
CV_RGB(255,0,0), 1, CV_AA,0);
}
} // free memory
cvReleaseMemStorage(&stor);
cvReleaseImage( &pyr );
}
int main(int argc, char** argv)
{
IplImage* motion = 0;
CvCapture* capture = 0; //视频获取结构
if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
//原型:extern int isdigit(char c); //用法:#include <ctype.h> 功能:判断字符c是否为数字 说明:当c为数字0-9时,返回非零值,否则返回零。
capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 1 );
else if( argc == 2 )
capture = cvCaptureFromAVI( argv[1] );
if( capture )
{
cvNamedWindow( "Motion", 1 );
for(;;)
{
IplImage* image;
if( !cvGrabFrame( capture )) //从摄像头或者视频文件中抓取帧
break;
image = cvRetrieveFrame( capture );
//取回由函数cvGrabFrame抓取的图像,返回由函数cvGrabFrame 抓取的图像的指针
if( image )
{
if( !motion )
{
motion = cvCreateImage( cvSize(image->width,image->height), 8, 1 );
cvZero( motion );
motion->origin = image->origin;
///* 0 - 顶—左结构, 1 - 底—左结构 (Windows bitmaps 风格) */
}
}
update_mhi( image, motion, 60 );
cvShowImage( "Motion", image );
if( cvWaitKey(10) >= 0 )
break;
}
cvReleaseCapture( &capture );
cvDestroyWindow( "Motion" );
}
return 0;
}
#include "cv.h"
#include <cxcore.h>
#include "highgui.h"
#include <time.h>
#include <math.h>
#include <ctype.h>
#include <stdio.h>
#include <string.h>
// various tracking parameters (in seconds)
const double MHI_DURATION = 0.5;
const double MAX_TIME_DELTA = 0.5;
const double MIN_TIME_DELTA = 0.05;
const int N = 3;
//
const int CONTOUR_MAX_AERA = 16;
// ring image buffer
IplImage **buf = 0;
int last = 0;
// temporary images
IplImage *mhi = 0;
// MHI: motion history image
int filter = CV_GAUSSIAN_5x5;
CvConnectedComp *cur_comp, min_comp;
CvConnectedComp comp;
CvMemStorage *storage; CvPoint pt[4];
// 参数:
// img – 输入视频帧
// dst – 检测结果
void update_mhi( IplImage* img, IplImage* dst, int diff_threshold )
{
double timestamp = clock()/100.;
// get current time in seconds
CvSize size = cvSize(img->width,img->height);
// get current frame size
int i, j, idx1, idx2;
IplImage* silh;
uchar val;
float temp;
IplImage* pyr = cvCreateImage( cvSize((size.width & -2)/2, (size.height & -2)/2), 8, 1 );
CvMemStorage *stor;
CvSeq *cont, *result, *squares;
CvSeqReader reader;
if( !mhi || mhi->width != size.width || mhi->height != size.height )
{
if( buf == 0 )
{
buf = (IplImage**)malloc(N*sizeof(buf[0]));
memset( buf, 0, N*sizeof(buf[0]));
}
for( i = 0; i < N; i++ )
{
cvReleaseImage( &buf[i] );
buf[i] = cvCreateImage( size, IPL_DEPTH_8U, 1 );
cvZero( buf[i] );
}
cvReleaseImage( &mhi );
mhi = cvCreateImage( size, IPL_DEPTH_32F, 1 );
cvZero( mhi );
// clear MHI at the beginning
}
// end of if(mhi)
cvCvtColor( img, buf[last], CV_BGR2GRAY );
// convert frame to grayscale
idx1 = last;
idx2 = (last + 1) % N;
// index of (last - (N-1))th frame
last = idx2;
// 做帧差
silh = buf[idx2];
cvAbsDiff( buf[idx1], buf[idx2], silh );
// get difference between frames
// 对差图像做二值化
cvThreshold( silh, silh, 30, 255, CV_THRESH_BINARY );
// and threshold it
cvUpdateMotionHistory( silh, mhi, timestamp, MHI_DURATION );
// update MHI
cvCvtScale( mhi, dst, 255./MHI_DURATION,
(MHI_DURATION - timestamp)*255./MHI_DURATION );
cvCvtScale( mhi, dst, 255./MHI_DURATION, 0 );
// 中值滤波,消除小的噪声
cvSmooth( dst, dst, CV_MEDIAN, 3, 0, 0, 0 );
// 向下采样,去掉噪声
cvPyrDown( dst, pyr, 7 );
cvDilate( pyr, pyr, 0, 1 );
// 做膨胀操作,消除目标的不连续空洞
cvPyrUp( pyr, dst, 7 );
//
// 下面的程序段用来找到轮廓
//
// Create dynamic structure and sequence.
stor = cvCreateMemStorage(0);
cont = cvCreateSeq(CV_SEQ_ELTYPE_POINT, sizeof(CvSeq), sizeof(CvPoint) , stor);
// 找到所有轮廓
cvFindContours( dst, stor, &cont, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0));
// 直接使用CONTOUR中的矩形来画轮廓
for(;cont;cont = cont->h_next)
{
CvRect r = ((CvContour*)cont)->rect;
if(r.height * r.width > CONTOUR_MAX_AERA) // 面积小的方形抛弃掉
{
cvRectangle( img, cvPoint(r.x,r.y),
cvPoint(r.x + r.width, r.y + r.height),
CV_RGB(255,0,0), 1, CV_AA,0);
}
} // free memory
cvReleaseMemStorage(&stor);
cvReleaseImage( &pyr );
}
int main(int argc, char** argv)
{
IplImage* motion = 0;
CvCapture* capture = 0; //视频获取结构
if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
//原型:extern int isdigit(char c); //用法:#include <ctype.h> 功能:判断字符c是否为数字 说明:当c为数字0-9时,返回非零值,否则返回零。
capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 1 );
else if( argc == 2 )
capture = cvCaptureFromAVI( argv[1] );
if( capture )
{
cvNamedWindow( "Motion", 1 );
for(;;)
{
IplImage* image;
if( !cvGrabFrame( capture )) //从摄像头或者视频文件中抓取帧
break;
image = cvRetrieveFrame( capture );
//取回由函数cvGrabFrame抓取的图像,返回由函数cvGrabFrame 抓取的图像的指针
if( image )
{
if( !motion )
{
motion = cvCreateImage( cvSize(image->width,image->height), 8, 1 );
cvZero( motion );
motion->origin = image->origin;
///* 0 - 顶—左结构, 1 - 底—左结构 (Windows bitmaps 风格) */
}
}
update_mhi( image, motion, 60 );
cvShowImage( "Motion", image );
if( cvWaitKey(10) >= 0 )
break;
}
cvReleaseCapture( &capture );
cvDestroyWindow( "Motion" );
}
return 0;
}
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本回答由苏州千视通视觉科技股份有限公司_提供
2014-04-05
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不清楚耶,但不明觉厉
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2014-04-20
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opencv里自带行人检测的,就是效果不好
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2014-04-21
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自带的里面就有的。在source里
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2014-04-21
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我想。。我有。。。
追问
效果好吗,能发我一个吗
追答
csdn里面搜搜吧,hog+svm分类器,,
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