c++ - BackgroundSubtractorMOG2 在 VS2012 下工作，在 ubuntu 上失败

Question

我编写了以下代码来从视频或相机中检测到一个人并在其周围绘制一个最小矩形。

它在装有 Visual Studio 2012 Express 和 OpenCV 2.4.9 的 Windows 7 64 位系统上运行良好。当我在 Ubuntu 13.04 64 位下与 Eclipse 3.8 和 OpenCV 主分支(whcih 是 3.0) 下使用相同的代码时，它说“'BackgroundSubtractorMOG2' 类型必须实现继承的纯虚拟方法 xxx”，其中xxx 继承自 'BackgroundSubtractor'。

来自@VictorL BackgroundSubtractorMOG2 & OpenCV ，他的 BackgroundSubtractorMOG2 代码在 ubuntu 12.10 64 位和 OpenCV 2.4.4a 下工作。

所以我想知道两个版本的 OpenCV 之间“BackgroundSubtractorMOG2”的实现是否不同，或者编译器与 Ubuntu 12.10 和 13.04 不同。谁有类似的问题，我该如何解决。

提前致谢。

/*
    1. Detection
        I just use Gaussian Mixture Model(Background Subtraction) here
*/
#include <iostream>

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/video/background_segm.hpp>

using namespace std;
using namespace cv;

int detection();

#define CAMERA 0

#if CAMERA
    VideoCapture cap(-1);
#else
    VideoCapture cap("group.webm");
#endif


int main(){
    if(detection() == -1){
        cout << "Detection failed" << endl;
        return 1;
    }
    return 0;
}

int detection(){
    //check whether the camera is opened
    if(!cap.isOpened()){
        cout << "Camera failed to open" << endl;
        return -1;
    }

    Mat originalVideo, currentMat, diffMat, bgMat, binMat, erodeMat, morphMat;
    Mat filledMat;
    vector<vector<Point> > contours;

    namedWindow("currentMat", WINDOW_NORMAL);
    namedWindow("diffMat", WINDOW_NORMAL);
    namedWindow("erodeMat", WINDOW_NORMAL);
    namedWindow("erodeMat2", WINDOW_NORMAL);
    namedWindow("erodeMat3", WINDOW_NORMAL);
    namedWindow("dilate", WINDOW_NORMAL);
    namedWindow("binMat", WINDOW_NORMAL);
    //Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
    BackgroundSubtractorMOG2 gaussianBgModel;
    gaussianBgModel.set("nmixtures", 3);

    while(1){
        // get a new frame from camera
        cap >> currentMat;
        if(currentMat.empty())
            break;
        imshow("currentMat", currentMat);
        //get the foreground mask
        gaussianBgModel.operator()(currentMat, diffMat);
        imshow("diffMat", diffMat);
        gaussianBgModel.getBackgroundImage(bgMat);
        //do threshold to get binary imahe
        threshold(diffMat, binMat, 252, 255, 0); // Threshold Type 0: Binary
        imshow("binMat", binMat);
        blur(binMat, erodeMat, Size(4, 4));
        imshow("erodeMat", erodeMat);
        threshold(erodeMat, erodeMat, 256/6, 255, 0);
        imshow("erodeMat2", erodeMat);
        int operation = 1 + 2;
        int morph_size = 1;
        Mat element = getStructuringElement(0,
                Size(4 * morph_size + 1, 8 * morph_size + 1),
                Point(morph_size, morph_size));
        Mat elementrect = getStructuringElement(0,
                Size(2 * morph_size + 1, 16 * morph_size + 1),
                Point(morph_size, morph_size));
        dilate(erodeMat, morphMat, element);
        imshow("dilate", morphMat);
        erode(morphMat, morphMat, elementrect);
        imshow("erodeMat3", morphMat);
//--------AFTER ABOVE, PEOPLE IS IDENTIFIED--------------------
//--------NEXT TO FIND COUNTOUR
        // Find contours
        //get a copy of the filtered img
        filledMat = morphMat.clone();

        findContours(filledMat, contours, CV_RETR_TREE,
                CV_CHAIN_APPROX_SIMPLE);
        vector<vector<Point> > contours_poly(contours.size());
        vector<Rect> boundRect(contours.size());
        vector<Point2f> centers(contours.size());
        //      cascadeMat = Mat::zeros(filledMat.size(), 1);
        // Get Bound Rect
        for (unsigned i = 0; i < contours.size(); i++) {
            approxPolyDP(Mat(contours[i]), contours_poly[i], 3, true);
            boundRect[i] = boundingRect(Mat(contours_poly[i]));
        }
        /// Draw polygonal contour + bonding rects
        Mat drawing = Mat::zeros( filledMat.size(), CV_8UC3 );
        for(unsigned i = 0; i< contours.size(); i++ ){
            Scalar color = Scalar( 255, 0, 0 );
            //drawContours( drawing, contours_poly, i, color, 1, 8, vector<Vec4i>(), 0, Point() );
            if(boundRect[i].area() > 3000){
                rectangle( drawing, boundRect[i].tl(), boundRect[i].br(), color, 2, 8, 0 );
                Mat roi(currentMat, boundRect[i]);
                namedWindow("ROI", CV_WINDOW_NORMAL);
                imshow( "ROI", roi );
            }
        }

        /// Show in a window
        namedWindow( "Contours", CV_WINDOW_NORMAL );
        imshow( "Contours", drawing );


        if(waitKey(30) >= 0) break;
    }
    return 0;
}

Answer 1

如果您不想降级 opencv，对于 opencv 3.0，您可能需要关注 opencv documentation

主要区别是:

pMOG2 = createBackgroundSubtractorMOG2();      //create Background Subtractor objects

pMOG2->apply(frame, fgMaskMOG2);               //update the background model

确保链接必要的库。