Question

我编写了以下代码来检测视频或摄像机中的人物并在其周围绘制最小矩形。

在Visual Studio 2012 Express和OpenCV 2.4.9的Windows 7 64位上运行良好。当我使用64位的Ubuntu 13.04和Eclipse 3.8以及 OpenCV主分支（whcih是3.0）时使用相同的代码时，它说“类型'BackgroundSubtractorMOG2'必须实现继承的纯虚方法xxx”，其中xxx继承自'BackgroundSubtractor'。

来自@VictorL BackgroundSubtractorMOG2 & OpenCV，他的BackgroundSubtractorMOG2代码在ubuntu 12.10 64位下使用OpenCV 2.4.4a工作。

所以我想知道两个版本的OpenCV之间'BackgroundSubtractorMOG2'的实现是不同的，或者编译器与Ubuntu 12.10和13.04不同。任何人都有类似的问题，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。

BackgroundSubtractorMOG2在VS2012下工作，在ubuntu上失败

1 个答案: