opencv3/C++关于移动对象的轮廓的跟踪详解

#include<opencv2/opencv.hpp>using namespace cv;//基于移动对象的轮廓的跟踪int main(){  Mat frame;  bool flag = true;  VideoCapture capture;  capture.open(0);  if (!capture.isOpened())  {    printf("can not open ....../n");    return -1;  }  namedWindow("mask", WINDOW_AUTOSIZE);  namedWindow("output", WINDOW_AUTOSIZE);   Ptr<BackgroundSubtractor> pKNN = createBackgroundSubtractorKNN();  //Ptr<BackgroundSubtractor> pMOG2 = createBackgroundSubtractorMOG2();  while (capture.read(frame))  {    Mat KNNMask;    std::vector<std::vector<Point>>contours;    pKNN->apply(frame, KNNMask);    //(*pMOG2).apply(frame, mogMask);    threshold(KNNMask, KNNMask, 100, 255, THRESH_BINARY);    Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3));    morphologyEx(KNNMask, KNNMask, MORPH_OPEN, kernel, Point(-1,-1));    findContours(KNNMask, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0,0));    for (int i = 0; i < contours.size(); i++)    {      //轮廓面积      double area = contourArea(contours[i]);      //轮廓外接矩阵      Rect rect = boundingRect(contours[i]);      if (area < 500 || rect.width < 50 || rect.height < 50) continue;      rectangle(frame, rect, Scalar(0,255,255),2);      putText(frame, "Target", Point(rect.x, rect.y), CV_FONT_NORMAL, FONT_HERSHEY_PLAIN, Scalar(0,255,0),2,8);    }    imshow("mask",KNNMask);    imshow("output",frame);    waitKey(1);  }  return 0;}