0058-用OpenCV的级联分类器CascadeClassifier做人脸和人眼的识别

级联分类器可以用来识别人脸区域和人眼区域，OpenCV提供了类CascadeClassifier，它是Opencv中做人脸检测的时候的一个级联分类器，相关的原理请大家自行查阅相关资料。

使用级联分类器时要先加载训练好的xml分类器文件。

示例代码如下：
代码中用的视频下载链接：https://pan.baidu.com/s/1bo7rRtl 密码：6zyj
代码是用到的xml分类器文件下载链接：https://pan.baidu.com/s/1nvSm1bN 分享密码请搜索公众号"qxsf321"，关注后回复0058即可获取

//opencv版本:OpenCV3.0
//VS版本:VS2013
//Author:qxsf321.net#include <opencv2/opencv.hpp>  
#include <opencv2/imgproc/types_c.h>#include <opencv2/imgproc/types_c.h>
#include <opencv2/highgui/highgui_c.h>
#include <opencv2/objdetect/objdetect_c.h>#include <iostream>using namespace cv;
using namespace std;/** Function Headers */
void detectAndDisplay(Mat frame);/** Global variables */
//-- Note, either copy these two files from opencv/data/haarscascades to your current folder, or change these locations
String face_cascade_name = "haarcascade_frontalface_alt.xml";
String eyes_cascade_name = "haarcascade_eye_tree_eyeglasses.xml";
CascadeClassifier face_cascade;
CascadeClassifier eyes_cascade;
string window_name = "Capture - Face detection";
RNG rng(12345);int main(int argc, const char** argv)
{Mat frame;//-- 1. Load the cascadesif (!face_cascade.load(face_cascade_name)){ printf("--(!)Error loading\n"); return -1; };if (!eyes_cascade.load(eyes_cascade_name)){ printf("--(!)Error loading\n"); return -1; };//-- 2. Read the video stream//         CvCapture* capture = cvCaptureFromCAM( -1 );        // 摄像头读取文件开关VideoCapture capture("Sample.avi");if (capture.isOpened()/*capture*/)        // 摄像头读取文件开关{while (true){//                         frame = cvQueryFrame( capture );        // 摄像头读取文件开关capture >> frame;//-- 3. Apply the classifier to the frameif (!frame.empty()){detectAndDisplay(frame);}else{printf(" --(!) No captured frame -- Break!"); break;}int c = waitKey(10);if ((char)c == 'c') { break; }}}return 0;
}/**
* @function detectAndDisplay
*/
void detectAndDisplay(Mat frame)
{std::vector<Rect> faces;Mat frame_gray;cvtColor(frame, frame_gray, CV_BGR2GRAY);equalizeHist(frame_gray, frame_gray);//-- Detect facesface_cascade.detectMultiScale(frame_gray, 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(frame, 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 = frame_gray(faces[i]);std::vector<Rect> eyes;//-- In each face, detect eyeseyes_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(frame, center, radius, Scalar(255, 0, 0), 3, 8, 0);}}//-- Show what you gotimshow(window_name, frame);
}

运行结果截图如下：