在博客《視頻人數統計（opencv）》中，作者使用的Absdiff幀差法降低背景影響，進而通過二值化，邊緣化，濾波器，形態學變化，查找輪廓，輪廓面積控制，繪制輪廓等一系列方法完成了對樣例圖片的處理，並實現了人數統計的功能。同樣的，筆者最初也是和這位作者采用了同樣的方法來做，但是在筆者的樣例視頻中統計的效果並不是很理性。之后筆者使用了前后背景分離的方法來代替Absdiff幀差法，最后得到了較為理想的效果。閑話不多說，直接上代碼了。

using namespace std;
using namespace cv;

int main(int argc, const char** argv)
{
    VideoCapture cap;
    bool update_bg_model = true;

    //cap.open(0);
    cap.open("People.mp4");

    if( !cap.isOpened() )
    {
        printf("can not open camera or video file\n");
        return -1;
    }

    namedWindow("image", WINDOW_AUTOSIZE);
    namedWindow("foreground mask", WINDOW_AUTOSIZE);
    namedWindow("foreground image", WINDOW_AUTOSIZE);
    namedWindow("mean background image", WINDOW_AUTOSIZE);

    BackgroundSubtractorMOG2 bg_model;//(100, 3, 0.3, 5);建立背景模型

    Mat img, fgmask, fgimg;
    int i = 0;

    for(;;)
    {
        i++;
        cap >> img;

        if( img.empty() )
            break;

        img = img(Rect(40, 0, 300, img.rows));

        if( fgimg.empty() )
            fgimg.create(img.size(), img.type());

        //更新模型
        bg_model(img, fgmask, update_bg_model ? -1 : 0);
        medianBlur(fgmask, fgmask, 13);
        threshold(fgmask, fgmask, 150, 255, THRESH_BINARY);

        Mat element = getStructuringElement(MORPH_RECT, Size(3, 3));

        /*erode(fgmask, fgmask, element, Point(0, 0), 3);
 dilate(fgmask, fgmask, element, Point(0, 0), 3);*/

        Mat srcGrayImage = fgmask.clone();
        vector<vector<Point>> vContours;
        vector<Vec4i> vHierarchy;
        findContours(srcGrayImage, vContours, vHierarchy, RETR_CCOMP, CHAIN_APPROX_SIMPLE, Point(0, 0));

        int count = 0;
        RNG rng(12345);

        for (int i = 0; i < vContours.size(); i++)
        {
            double area = contourArea(vContours[i], false);

            RotatedRect smallRect = minAreaRect(vContours[i]);
            Point2f smallRect_center = smallRect.center;
            float smallRect_width = smallRect.size.width;
            float smallRect_height = smallRect.size.height;
            float smallRect_angle = 0;

            smallRect = RotatedRect(smallRect_center, Size2f(smallRect_height, smallRect_width), smallRect_angle);
            Point2f P[4];
            smallRect.points(P);

            if (area>1000 && area < 4200)
            {
                count++;
                for (int j = 0; j <= 3; j++)
                {
                    line(img, P[j], P[(j + 1) % 4], Scalar(255, 0, 0), 2);
                }
            }
            if (area>4200 && area < 6000)
            {
                count+=2;
                for (int j = 0; j <= 3; j++)
                {
                    line(img, P[j], P[(j + 1) % 4], Scalar(255, 0, 0), 2);
                }
            }

        }

        Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));//任意值
        putText(img, int2str(count), Point(220, 40), FONT_HERSHEY_TRIPLEX, 1, color, 2);

        fgimg = Scalar::all(0);
        img.copyTo(fgimg, fgmask);

        Mat bgimg;
        bg_model.getBackgroundImage(bgimg);

        imshow("image", img);

        /*string windows_name = "Video/image_" + int2str(i);
 string windows_name_ext = windows_name + ".jpg";
 imwrite(windows_name_ext, img);*/

        imshow("foreground mask", fgmask);


        imshow("foreground image", fgimg);
        if(!bgimg.empty())
            imshow("mean background image", bgimg );

        char k = (char)waitKey(1);
        if( k == 27 ) break;
        if( k == ' ' )
        {
            update_bg_model = !update_bg_model;
            if(update_bg_model)
                printf("\t>背景更新(Background update)已打開\n");
            else
                printf("\t>背景更新(Background update)已關閉\n");
        }
    }

    return 0;
}

最后，讓我們來看看運行結果：

1個人

2個人

3個人

4個人

附加個人視頻人數統計展示地址：
http://www.bilibili.com/video/av11568593/
http://www.bilibili.com/video/av11593676/

參考：
【1】http://blog.csdn.net/u013812682/article/details/51980765
【2】 @淺墨_毛星雲《OpenCV3編程入門》OpenCV2版書本附贈示例程序20