Motion tracking (six): BackgroundSubtractorMOG(), background difference

class CV_EXPORTS_W BackgroundSubtractorMOG : public BackgroundSubtractor
{
public:
    //! the default constructor
    CV_WRAP BackgroundSubtractorMOG();
    //! the full constructor that takes the length of the history, the number of gaussian mixtures, the background ratio parameter and the noise strength
    CV_WRAP BackgroundSubtractorMOG(int history, int nmixtures, double backgroundRatio, double noiseSigma=0);
    //! the destructor
    virtual ~BackgroundSubtractorMOG();
    //! the update operator
    virtual void operator()(InputArray image, OutputArray fgmask, double learningRate=0);

    //! re-initiaization method
    virtual void initialize(Size frameSize, int frameType);

    virtual AlgorithmInfo* info() const;

protected:
    Size frameSize;
    int frameType;
    Mat bgmodel;
    int nframes;
    int history;
    int nmixtures;
    double varThreshold;
    double backgroundRatio;
    double noiseSigma;
};

(1) BackgroundSubtractorMOG() example

// background_segment_objects.cpp : Defines the entry point for the console application.
//

#include "stdafx.h"

#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/video/background_segm.hpp"
#include <stdio.h>
#include <string>

using namespace cv;

static void help()
{
	printf("\n"
		"This program demonstrated a simple method of connected components clean up of background subtraction\n"
		"When the program starts, it begins learning the background.\n"
		"You can toggle background learning on and off by hitting the space bar.\n"
		"Call\n"
		"./segment_objects [video file, else it reads camera 0]\n\n");
}

static void refineSegments(const Mat& img, Mat& mask, Mat& dst)
{
	int niters = 3;

	vector<vector<Point> > contours;
	vector<Vec4i> hierarchy;

	Mat temp;

	dilate(mask, temp, Mat(), Point(-1,-1), niters);
	erode(temp, temp, Mat(), Point(-1,-1), niters*2);
	dilate(temp, temp, Mat(), Point(-1,-1), niters);

	findContours( temp, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );

	dst = Mat::zeros(img.size(), CV_8UC3);

	if( contours.size() == 0 )
		return;

	// iterate through all the top-level contours,
	// draw each connected component with its own random color
	int idx = 0, largestComp = 0;
	double maxArea = 0;

	for( ; idx >= 0; idx = hierarchy[idx][0] )
	{
		const vector<Point>& c = contours[idx];
		double area = fabs(contourArea(Mat(c)));
		if( area > maxArea )
		{
			maxArea = area;
			largestComp = idx;
		}
	}
	Scalar color( 0, 0, 255 );
	drawContours( dst, contours, largestComp, color, CV_FILLED, 8, hierarchy );
}


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

	help();

	if( argc < 2 )
		cap.open(0);
	else
		cap.open(std::string(argv[1]));

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

	Mat tmp_frame, bgmask, out_frame;

	cap >> tmp_frame;
	if(!tmp_frame.data)
	{
		printf("can not read data from the video source\n");
		return -1;
	}

	namedWindow("video", 1);
	namedWindow("segmented", 1);

	BackgroundSubtractorMOG bgsubtractor;
	bgsubtractor.set("noiseSigma", 10);

	for(;;)
	{
		cap >> tmp_frame;
		if( !tmp_frame.data )
			break;
		bgsubtractor(tmp_frame, bgmask, update_bg_model ? -1 : 0);
		refineSegments(tmp_frame, bgmask, out_frame);
		imshow("video", tmp_frame);
		imshow("segmented", out_frame);
		int keycode = waitKey(30);
		if( keycode == 27 )
			break;
		if( keycode == ' ' )
		{
			update_bg_model = !update_bg_model;
			printf("Learn background is in state = %d\n",update_bg_model);
		}
	}

	return 0;
}

(2) Test effect