最近接觸移動偵測專案，其對應的原理主要是背景建模，而背景建模方法眾多，常見的如幀差法、背景減除法、codebook、Vibe、GMM等。
前景提取的步驟如下：

#include "opencv2/opencv.hpp"

using namespace cv;
using namespace std;

void updateBG(Mat src, Mat &dst, double alpha);
void drawRect(Mat &src, Mat mask);

void main()
{
    VideoCapture cap("E:\\Database\\768x576.avi"
 
);
    if (!cap.isOpened())
        return;

    Mat frame, gray_frame;
    Mat BgImg, FrImg_src, FrImg;

    Mat BgImg_32, FrImg_src_32, FrImg_32;

    bool firstflag = true;
    while (1)
    {
        cap >> frame;
        if (frame.empty())
            return;

        if (firstflag)
        {
            cvtColor(frame, BgImg, CV_BGR2GRAY);
            BgImg.convertTo(BgImg_32, CV_32FC1);   //BgImg、FrImg、FrImg_src都已經轉換為CV_32FC1.
 

            firstflag = false;

            FrImg_32 = BgImg_32.clone();
            FrImg_src_32 = BgImg_32.clone();
        }
        else
        {
            cvtColor(frame, gray_frame, CV_BGR2GRAY);
            gray_frame.convertTo(gray_frame, CV_32FC1);

            absdiff(gray_frame, BgImg_32, FrImg_src_32);
            threshold(FrImg_src_32, FrImg_32, 50
 
, 255.0, CV_THRESH_BINARY);
            updateBG(gray_frame, BgImg_32, 0.005);

            BgImg_32.convertTo(BgImg, CV_8UC1);
            FrImg_32.convertTo(FrImg, CV_8UC1);
            FrImg_src_32.convertTo(FrImg_src, CV_8UC1);

            drawRect(frame, FrImg);

            imshow("SRC", frame);
            imshow("BG", BgImg);
            imshow("FG", FrImg);
            imshow("FG_Src", FrImg_src);

            waitKey(10);
        }

    }
}
//dst = dst*(1-alpha) + src*alpha
void updateBG(Mat src, Mat &dst, double alpha)
{
    for (int i = 0; i < src.rows;i++)
    {
        float* ptr1 = src.ptr<float>(i);
        float* ptr2 = dst.ptr<float>(i);
        for (int j = 0; j < src.cols; j++)
        {
            ptr2[j] = ptr1[j] * alpha + (1 - alpha)*ptr2[j];
        }
    }

}
void drawRect(Mat &src, Mat mask)
{
    vector<vector<Point>> contours;
    findContours(mask, contours, CV_RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
    for (int i = 0; i < contours.size(); i++)
    {
        Rect r(0, 0, 0, 0);
        if (contourArea(contours[i])>100)
        {
            int x_min = 1000;
            int x_max = 0;
            int y_min = 1000;
            int y_max = 0;
            //找最大外接矩形
            for (int j = 0; j < contours[i].size(); j++)
            {
                x_min = x_min > contours[i][j].x ? contours[i][j].x : x_min;
                x_max = x_max < contours[i][j].x ? contours[i][j].x : x_max;
                y_min = y_min > contours[i][j].y ? contours[i][j].y : y_min;
                y_max = y_max < contours[i][j].y ? contours[i][j].y : y_max;
            }
            r.x = x_min;
            r.y = y_min;
            r.width = x_max - x_min;
            r.height = y_max - y_min;
        }
        rectangle(src, r, Scalar(0, 255, 0), 2, 8);
    }
}

效果還是很不錯的，可以有效自適應光照的變化。