背景减法后如何检测分割对象？

Question

我正在尝试使用opencv 2.4.2进行对象检测。这是我的移动前景减法的代码。现在我想检测原始帧中的移动物体并在其周围绘制边界框。 任何人都可以帮我吗？怎么做？

#include "stdafx.h" 
    #include "opencv2/imgproc/imgproc.hpp" 
    #include "opencv2/highgui/highgui.hpp" 
    #include "opencv2/contrib/contrib.hpp" 
    #include "conio.h" 

    #include "time.h" 
    #include "opencv/cvaux.hpp" 
    #include "opencv2/core/core.hpp" 
    #include "opencv2/calib3d/calib3d.hpp" 

    using namespace std; 
using namespace cv; 
    int main(int argc, char *argv[]) 
    { 


    int key = 0; 

    CvSize imgSize; 
    CvCapture* capture = cvCaptureFromFile("S:\\offline object detection database\\TwoEnterShop2cor.MPG"); 

     IplImage* frame = cvQueryFrame(capture); 
     imgSize = cvGetSize(frame); 

     IplImage* grayImage = cvCreateImage(imgSize, IPL_DEPTH_8U, 1); 
     IplImage* currframe = cvCreateImage(imgSize,IPL_DEPTH_8U,3); 
     IplImage* destframe = cvCreateImage(imgSize,IPL_DEPTH_8U,3); 
    if (!capture) 

    { 
    fprintf(stderr, "Cannot open AVI!\n"); 
    return 1; 
    } 


    int fps = (int)cvGetCaptureProperty(capture, CV_CAP_PROP_FPS); 

    cvNamedWindow("dest", CV_WINDOW_AUTOSIZE); 

    while(key != 'y') 
    { 
    frame = cvQueryFrame(capture); 

    currframe = cvCloneImage(frame);// copy frame to current 
    frame = cvQueryFrame(capture);// grab frame 
    cvAbsDiff(frame,currframe,destframe); 

cvCvtColor(destframe,grayImage,CV_RGB2GRAY); 
cvSmooth(grayImage,grayImage,CV_MEDIAN,3,3,0); 
    cvAdaptiveThreshold(grayImage,grayImage,230,CV_THRESH_BINARY,CV_ADAPTIVE_THRESH_GAUSSIAN_C,3,5); 

    cvDilate(grayImage, grayImage, 0,1); 
cvErode(grayImage,grayImage, 0, 0); 
    if(key==27)break; 
    cvShowImage("fram",currframe); 
    cvShowImage("dest",grayImage); 
    key = cvWaitKey(100); 
    } 
    cvDestroyWindow("dest"); 
    cvReleaseCapture(&capture); 
    return 0; 
    } 

Answer 1

帧差是背景差的最简单的方法，但它是你使用的门槛非常敏感，可能不会得到了良好的效果更好的方法是估计的背景模型，比较每一帧和背景模型来确定移动对象。

您可以从以下链接找到更多信息：
Background subtraction in OpenCV(C++)
Background Subtraction with OpenCV 2