opencv背景去除建模（BSM）

opencv提供两种BS算法：

1.基于图像分割（GMM-高斯混合模型）；

2.机器学习（KNN-K近邻）。

下面是基于以上两种BS算法的示例代码：

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

int main()
{
    VideoCapture capture;

    capture.open("1.avi");
    if(!capture.isOpened())
    {
        cout << "could not find the video file ..." << endl;
        return -1;
    }

    Mat frame;
    Mat bsmaskMOG2;
    Mat bsmaskKNN;

    namedWindow("input video", CV_WINDOW_AUTOSIZE);
    namedWindow("MOG2", CV_WINDOW_AUTOSIZE);
    namedWindow("KNN", CV_WINDOW_AUTOSIZE);

    Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));//形态学开操作

    //init BS
    Ptr<BackgroundSubtractor> pMOG2 = createBackgroundSubtractorMOG2();
    Ptr<BackgroundSubtractor> pKNN = createBackgroundSubtractorKNN();

    while(capture.read(frame))
    {
        imshow("input video", frame);

        //BSM MOG
        pMOG2->apply(frame, bsmaskMOG2);
        morphologyEx(bsmaskMOG2, bsmaskMOG2, MORPH_OPEN,kernel, Point(-1, -1));//形态学开操作去噪点
        imshow("MOG2", bsmaskMOG2);

        //BSM KNN
        pKNN->apply(frame, bsmaskKNN);
        morphologyEx(bsmaskKNN, bsmaskKNN, MORPH_OPEN,kernel, Point(-1, -1));//形态学开操作去噪点
        imshow("KNN", bsmaskKNN);

        char c = waitKey(100);
        if(c == 27)
        {
            break;
        }
    }

    capture.release();

    waitKey(0);

    return 0;
}