OpenCV脸部、眼睛检测
时间:2014-04-27 20:40:47
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/* 功能:实现对眼睛、脸部的跟踪。 版本:1.0 时间:2014-4-27 */ #include <opencv2/objdetect/objdetect.hpp> #include <opencv2/highgui/highgui.hpp> #include <opencv2/imgproc/imgproc.hpp> #include <opencv2/core/core.hpp> #include <iostream> #include <stdio.h> using namespace std; using namespace cv; void detectEyeAndFace( Mat frame ); //将下面两个文件复制到当前工程下。 //当前文件路径应该是OpenCV安装路径下的sources\data\haarcascades目录下 String face_cascade_name = "haarcascade_frontalface_alt.xml"; String eyes_cascade_name = "haarcascade_eye_tree_eyeglasses.xml"; CascadeClassifier face_cascade; CascadeClassifier eyes_cascade; RNG rng(12345); int main( int argc, const char** argv ) { Mat oneFrame; /* Mat test; test=imread("a.jpg"); imshow("",test); waitKey(0); */ //判断face_cascade_name、eye_cascade_name能够顺利加载 if( !face_cascade.load( face_cascade_name ) ){ printf("face_cascade_name加载失败\n"); return -1; }; if( !eyes_cascade.load( eyes_cascade_name ) ){ printf("eye_cascade_name加载失败\n"); return -1; }; VideoCapture vCp("Sample.avi"); if( vCp.isOpened()) { while( true ) { vCp>>oneFrame; //-- 3. Apply the classifier to the frame if( !oneFrame.empty() ) { detectEyeAndFace( oneFrame ); } else { printf(" 当前视频文件为空!"); break; } int c = waitKey(10); if( (char)c == ‘b‘ ) { break; } } } return 0; } void detectEyeAndFace( Mat oneFrame ) { std::vector<Rect> faces; //脸部标注框 Mat grayFrame; cvtColor( oneFrame, grayFrame, CV_BGR2GRAY ); equalizeHist( grayFrame, grayFrame ); face_cascade.detectMultiScale( grayFrame, faces, 1.1, 2, 0|CV_HAAR_SCALE_IMAGE, Size(30, 30) ); for( size_t i = 0; i < faces.size(); i++ ) { Point center( int(faces[i].x + faces[i].width*0.5), int(faces[i].y + faces[i].height*0.5) ); ellipse( oneFrame, center, Size( int(faces[i].width*0.5), int(faces[i].height*0.5)), 0, 0, 360, Scalar( 255, 0, 255 ), 2, 8, 0 ); Mat faceROI = grayFrame( faces[i] ); //得到当前标注的脸部区域 std::vector<Rect> eyes;//眼睛标注 eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CV_HAAR_SCALE_IMAGE, Size(30, 30) ); for( size_t j = 0; j < eyes.size(); j++ ) { Point center( int(faces[i].x + eyes[j].x + eyes[j].width*0.5), int(faces[i].y + eyes[j].y + eyes[j].height*0.5) ); int radius = cvRound( (eyes[j].width + eyes[i].height)*0.25 ); circle( oneFrame, center, radius, Scalar( 255, 0, 0 ), 3, 8, 0 ); } } imshow( "眼镜和脸部跟踪检测", oneFrame ); }
参考文献:
1.迭代的是人,递归的是神》OpenCV学习笔记(二十七)——基于级联分类器的目标检测objdect
http://blog.csdn.net/yang_xian521/article/details/6973667
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