人脸检测的C/C++源代码，曾发表于 OPENCV 的 MAILING LIST，主要是对OPENCV 3.1 版本发布的代码做了一些速度上的优化，并且解决了内存泄漏的问题。这个程序所使用的 Paul Viola 提出（该论文“Rapid Object Detection using a Boosted Cascade of Simple Features”发表在 CVPR'01）的 Ada Boosted Cascade 算法可以说是目前最好最快的目标检测算法。 关于OPENCV的介绍，参考： http://blog.csdn.net/hunnish/archive/2004/09/13/102535.aspx 关于该算法的详细介绍，也可参考： http://www.merl.com/people/viola/research/publications/CVPR-2001.pdf 以及： http://www.assuredigit.com/forum/display_topic_threads.asp?ForumID=11&TopicID=325 http://www.assuredigit.com/forum/display_topic_threads.asp?ForumID=11&TopicID=463 运行文件下载： http://www.assuredigit.com/product_tech/Demo_Download_files/Face.exe 该程序可以对静止图像以及视频序列进行 face tracking。对视频序列，请先插入USB接口的摄像头。 ==== 在OPENCV 3.1 版本，VC6.0下编译通过 ==== ===
#ifdef _CH_
#define WIN32
#error "The file needs cvaux, which is not wrapped yet. Sorry"
#endif #ifndef _EiC
#include "cv.h"
#include "cvaux.h"
#include "highgui.h" #endif #ifdef _EiC
#define WIN32
#endif #define ORIG_WIN_SIZE 24
static CvMemStorage* storage = 0;
static CvHidHaarClassifierCascade* hid_cascade = 0; #define WINNAME"Result" void detect_and_draw( IplImage* image, IplImage* TempImage ); int main( int argc, char** argv )
{
CvCapture* capture = 0; CvHaarClassifierCascade* cascade =
cvLoadHaarClassifierCascade( "",
cvSize( ORIG_WIN_SIZE, ORIG_WIN_SIZE ));
hid_cascade = cvCreateHidHaarClassifierCascade( cascade, 0, 0, 0, 1 );
cvReleaseHaarClassifierCascade( &cascade ); cvNamedWindow( WINNAME, 1 );
storage = cvCreateMemStorage(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 )
{
IplImage *frame, *temp;
cvGrabFrame( capture );
frame = cvRetrieveFrame( capture );

temp = cvCreateImage( cvSize(frame->width/2,frame->height/2), 8, 3 ); for(;;)
{
if( !cvGrabFrame( capture ))
break;
frame = cvRetrieveFrame( capture );
if( !frame )
break; detect_and_draw( frame, temp ); if( cvWaitKey( 10 ) >= 0 )
{
//cvReleaseImage( &frame );
//cvReleaseImage( &temp );
cvReleaseCapture( &capture );
cvDestroyWindow(WINNAME);
return 0;
}
}
}
else
{
char* filename = argc == 2 ? argv[1] : (char*)"lena.jpg";
IplImage* image = cvLoadImage( filename, 1 );
IplImage* temp = cvCreateImage( cvSize(image->width/2,image->height/2), 8, 3 ); if( image )
{
cvFlip( image, image, 0 );
image->origin = IPL_ORIGIN_BL;
detect_and_draw( image, temp );
cvWaitKey(0);
cvReleaseImage( &image );
cvReleaseImage( &temp );
}
cvDestroyWindow(WINNAME);
return 0;
}
return 0;
} void detect_and_draw( IplImage* img, IplImage* temp )
{
int scale = 2;
CvPoint pt1, pt2;
int i; cvPyrDown( img, temp, CV_GAUSSIAN_5x5 );
#ifdef WIN32
cvFlip( temp, temp, 0 );
#endif
cvClearMemStorage( storage ); if( hid_cascade )
{
CvSeq* faces = cvHaarDetectObjects( temp, hid_cascade, storage,
1.2, 2, CV_HAAR_DO_CANNY_PRUNING );
for( i = 0; i < (faces ? faces->total : 0); i++ )
{
CvRect* r = (CvRect*)cvGetSeqElem( faces, i, 0 );
pt1.x = r->x*scale;
pt2.x = (r->x+r->width)*scale;
#ifdef WIN32
pt1.y = img->height - r->y*scale;
pt2.y = img->height - (r->y+r->height)*scale;
#else
pt1.y = r->y*scale;
pt2.y = (r->y+r->height)*scale;
#endif
cvRectangle( img, pt1, pt2, CV_RGB(255,255,0), 3 );
}
} cvShowImage(WINNAME, img );
//cvReleaseImage( &temp );
} #ifdef _EiC
main(1,"facedetect.c");
#endif