Face Detect base OpenCV

Face Detect base OpenCV

1. Face Detect

待提取

2. Code

#include "FaceDetect.h"
using namespace std;
int main(void)
{// variablesIplImage * pInpImg = 0;CvHaarClassifierCascade * pCascade = 0;  // the face detectorCvMemStorage * pStorage = 0;        // memory for detector to useCvSeq * pFaceRectSeq;               // memory-access interfacechar ImageFilename[]="AKB48.jpg";// initializationspInpImg = cvLoadImage(ImageFilename, CV_LOAD_IMAGE_COLOR);pStorage = cvCreateMemStorage(0);pCascade = (CvHaarClassifierCascade *)cvLoad(("data/haarcascades/haarcascade_l"),0, 0, 0);// validate that everything initialized properlyif (!pInpImg || !pStorage || !pCascade){printf("Initialization failed: %sn",(!pInpImg) ? "can't load image file" :(!pCascade) ? "can't load haar-cascade -- ""make sure path is correct" :"unable to allocate memory for data storage", ImageFilename);exit(-1);}pFaceRectSeq = cvHaarDetectObjects(pInpImg, pCascade, pStorage,1.1,                       // increase search scale by 10% each pass3,                         // merge groups of three detectionsCV_HAAR_DO_CANNY_PRUNING,  // skip regions unlikely to contain a facecvSize(200, 200), cvSize(300, 300));  // smallest size face to detect = 40x40,largest size face 使用默认；忽略；// display detected facesdisplayDetections(pInpImg, pFaceRectSeq);// clean up and release resourcescvReleaseImage(&pInpImg);if (pCascade) cvReleaseHaarClassifierCascade(&pCascade);if (pStorage) cvReleaseMemStorage(&pStorage);return 0;
}void displayDetections(IplImage * pInpImg, CvSeq * pFaceRectSeq)
{const char * DISPLAY_WINDOW = "Haar Window";int i;// create a window to display detected facescvNamedWindow(DISPLAY_WINDOW, CV_WINDOW_AUTOSIZE);// draw a rectangular outline around each detectionfor (i = 0; i<(pFaceRectSeq ? pFaceRectSeq->total : 0); i++){CvRect* r = (CvRect*)cvGetSeqElem(pFaceRectSeq, i);CvPoint pt1 = { r->x, r->y };CvPoint pt2 = { r->x + r->width, r->y + r->height };cvRectangle(pInpImg, pt1, pt2, CV_RGB(0, 255, 0), 3, 4, 0);}// display face detectionscvShowImage(DISPLAY_WINDOW, pInpImg);cvWaitKey(0);cvDestroyWindow(DISPLAY_WINDOW);
}

3. Parameters and Tuning

CVAPI(CvSeq*)cvHaarDetectObjects( const CvArr* image,

                     CvHaarClassifierCascade*cascade, CvMemStorage* storage,

                     double scale_factor CV_DEFAULT(1.1),

                     int min_neighbors CV_DEFAULT(3),int flags CV_DEFAULT(0),

                     CvSize min_size CV_DEFAULT(cvSize(0,0)),CvSize max_size CV_DEFAULT(cvSize(0,0)));

MinimumDetection Scale

一般使用默认值，在data/haarcascades/*.xml中有定义，如haarcascade_l

<size> 24 24 </size>. 

可以根据需要将该参数设置的比默认值稍大些，可以使用包含人脸的输入图像的宽或高作对比进行修改；如1/4图像的宽。但是在修改时，需要保证此宽高比与默认保持一致，此处的宽高比为1：1。

 ScaleIncrease Rate

规定以多快的速度增加尺度从而在图像中检测人脸，该因子越高，检测的速度越快，但若过高，则会漏掉人脸。一般使用默认值1.1(10%)；

Canny Pruning Flag

若设置为CV_HAAR_DO_CANNY_PRUNING，检测时，将略过不太可能包含人脸的区域，减少运算量；