卡尔曼滤波+opencv 实现人脸跟踪

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 #include "opencv2/objdetect/objdetect.hpp"
 #include "opencv2/highgui/highgui.hpp"
 #include "opencv2/imgproc/imgproc.hpp"
 #include "opencv2/video/tracking.hpp"
 #include
 #include

 using namespace std;
 using namespace cv;

 /** 函数声明 */
 void detectAndDisplay(Mat& frame);

 /** 全局变量 */
 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 = "Face detection with Kalman";
 RNG rng(12345);
 struct face{
     Point leftTop=0;
     int width=0;
     int height=0;
 };
 face preFace;
 /** @主函数 */
 int main()
 {
     //kalman参数设置

     int stateNum = 4;
     int measureNum = 2;
     KalmanFilter KF(stateNum, measureNum, 0);
     //Mat processNoise(stateNum, 1, CV_32F);
     Mat measurement = Mat::zeros(measureNum, 1, CV_32F);
     KF.transitionMatrix = *(Mat_<float>(stateNum, stateNum) << 1, 0, 1, 0,//A 状态转移矩阵
         0, 1, 0, 1,
         0, 0, 1, 0,
         0, 0, 0, 1);
     //这里没有设置控制矩阵B，默认为零
     setIdentity(KF.measurementMatrix);//H=[1,0,0,0;0,1,0,0] 测量矩阵
     setIdentity(KF.processNoiseCov, Scalar::all(1e-5));//Q高斯白噪声，单位阵
     setIdentity(KF.measurementNoiseCov, Scalar::all(1e-1));//R高斯白噪声，单位阵
     setIdentity(KF.errorCovPost, Scalar::all(1));//P后验误差估计协方差矩阵，初始化为单位阵
     randn(KF.statePost, Scalar::all(0), Scalar::all(0.1));//初始化状态为随机值

     //读入视频

     if (!face_cascade.load(face_cascade_name)){ cout << "--(!)Error loading\n" << endl; };
     Mat frame, frame2;
     VideoCapture cap;
     cap.open("me1.mp4");
     //cap.open("me2.mp4");
     //cap.open("me3.mp4");
     while (true){
         for (int i = 0; i < 1; i++){
             cap >> frame;
         }
         if (!frame.empty())
         {
             resize(frame, frame2, Size(), 0.5, 0.5, INTER_LINEAR);
             Mat prediction = KF.predict();
             Point predict_pt = Point((int)prediction.at<float>(0), (int)prediction.at<float>(1));
             detectAndDisplay(frame2);
             measurement.at<float>(0) = (float)preFace.leftTop.x;
             measurement.at<float>(1) = (float)preFace.leftTop.y;
             KF.correct(measurement);
             //画卡尔曼的效果
             Point center(predict_pt.x + preFace.width*0.5, predict_pt.y + preFace.height*0.5);
             ellipse(frame2, center, Size(preFace.width*0.3, preFace.height*0.3), 0, 0, 360, Scalar(0, 0, 255), 4, 8, 0);
             circle(frame2, center, 3, Scalar(0, 0, 255), -1);
             imshow(window_name, frame2);
             waitKey(1);
         }
         else
         {
             printf(" --(!) No frame -- Break!");
             break;
         }
     }
     return 0;
 }

 /** @函数 detectAndDisplay */
 void detectAndDisplay(Mat& frame)
 {
     std::vector faces;
     Mat frame_gray;
     int Max_area=0;
     int faceID=0;

     cvtColor(frame, frame_gray, CV_BGR2GRAY);
     equalizeHist(frame_gray, frame_gray);

     //-- 多尺寸检测人脸
     face_cascade.detectMultiScale(frame_gray, faces, 1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(30, 30));
     //找出最大的脸，可以去除不是脸的误检，这些误检一般比较小
     for (int i = 0; i < faces.size(); i++)
     {
         if ((int)(faces[i].width*faces[i].height) > Max_area){
             Max_area =(int) faces[i].width*faces[i].height;
             faceID=i;
         }
     }

     if (faces.size() > 0)//必须是检测到脸才绘制当前人脸圆圈，并且只能绘制最大的脸
     {
         preFace.leftTop.x = faces[faceID].x;
         preFace.leftTop.y = faces[faceID].y;
         preFace.height = faces[faceID].height;
         preFace.width = faces[faceID].width;
         Point center(faces[faceID].x + faces[faceID].width*0.5, faces[faceID].y + faces[faceID].height*0.5);
         ellipse(frame, center, Size(faces[faceID].width*0.5, faces[faceID].height*0.5), 0, 0, 360, Scalar(0, 255, 0), 1, 8, 0);
         circle(frame, center, 3, Scalar(0, 255,0), -1);
     }
     else{//没检测到人脸绘制之前的人脸
         Point center(preFace.leftTop.x + preFace.width*0.5, preFace.leftTop.y + preFace.height*0.5);
         ellipse(frame, center, Size(preFace.width*0.5, preFace.height*0.5), 0, 0, 360, Scalar(0, 255, 0), 1, 8, 0);
         circle(frame, center, 3, Scalar(0, 255, 0), -1);
     }


 }