a simple frame-differencing - opencv

Question

The background scene often evolves over time because, for instance, the lighting condition might change (for example,from sunrise to sunset), or because new objects could be added or removed from the background.
Therefore, it is necessary to dynamically build a model of the background scene.
based on above, I wrote a simple frame differencing code.It works good But it's very slow.
how can I make it faster? Any suggestions?
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/core/core.hpp>
#include <iostream>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/video/background_segm.hpp >
using namespace cv;
using namespace std;
#include <iostream>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/video/tracking.hpp>
int main()
{
cv::Mat gray; // current gray-level image
cv::Mat background; // accumulated background
cv::Mat backImage; // background image
cv::Mat foreground; // foreground image
// learning rate in background accumulation
double learningRate;
int threshold; // threshold for foreground extraction
cv::VideoCapture capture("video.mp4");
// check if video successfully opened
if (!capture.isOpened())
return 0;
// current video frame
cv::Mat frame;
double rate= capture.get(CV_CAP_PROP_FPS);
int delay= 1000/rate;
// foreground binary image
//cv::Mat foreground;
cv::Mat output;
bool stop(false);
while (!stop){
if(!capture.read(frame))
break;
cv::cvtColor(frame, gray, CV_BGR2GRAY);
cv::namedWindow("back");
cv::imshow("back",gray);
// initialize background to 1st frame
if (background.empty())
gray.convertTo(background, CV_32F);
// convert background to 8U
background.convertTo(backImage,CV_8U);
// compute difference between image and background
cv::absdiff(backImage,gray,foreground);
// apply threshold to foreground image
cv::threshold(foreground,output, 10,255,cv::THRESH_BINARY_INV);
// accumulate background
cv::accumulateWeighted(gray, background, 0.01, output);
cv::namedWindow("out");
cv::imshow("out",output);
if (cv::waitKey(delay)>=0)
stop= true;
}
}

Answer 1

I modified and corrected some parts of your code:
in the while loop you call to cv::namedWindow("back") and cv::namedWindow("out"), this is only necessary to do once.
you use if (background.empty()) to see if the array is empty or not, this is just necessary for the first cycle in which the matrix background is empty because in the remaining matrix will be filled, so that your code does not error the first cycle initialize to zero background=cv::Mat::zeros(rows,cols,CV_32F) taking into account the type and size that will be required in the iteration while loop. Also it does not affect the operation of accumulation.
Here the updated code:
int main()
{
cv::Mat gray; // current gray-level image
cv::Mat background; // accumulated background
cv::Mat backImage; // background image
cv::Mat foreground; // foreground image
// learning rate in background accumulation
double learningRate;
int threshold; // threshold for foreground extraction
cv::VideoCapture capture("C:/Users/Pedram91/Pictures/Camera Roll/videoplayback.mp4");////C:/Users/Pedram91/Downloads/Video/videoplayback.mp4//C:/FLIR.mp4
// check if video successfully opened
if (!capture.isOpened())
return 0;
// current video frame
cv::Mat frame;
double rate= capture.get(CV_CAP_PROP_FPS);
int delay= 1000/rate;
// foreground binary image
//cv::Mat foreground;
cv::Mat output;
bool stop(false);
cv::namedWindow("back");//This should go here,You only need to call once
cv::namedWindow("out");//This should go here,You only need to call once
int cols=capture.get(CV_CAP_PROP_FRAME_HEIGHT);
int rows=capture.get(CV_CAP_PROP_FRAME_WIDTH);
background=cv::Mat::zeros(rows,cols,CV_32F);//this will save the "if (background.empty())" in the while loop
while (!stop){
if(!capture.read(frame))
break;
cv::cvtColor(frame, gray, CV_BGR2GRAY);
cv::imshow("back",gray);
// initialize background to 1st frame
// if (background.empty())
gray.convertTo(background, CV_32F);
// convert background to 8U
background.convertTo(backImage,CV_8U);
// compute difference between image and background
cv::absdiff(backImage,gray,foreground);
// apply threshold to foreground image
cv::threshold(foreground,output, 10,255,cv::THRESH_BINARY_INV);
// accumulate background
cv::accumulateWeighted(gray, background, 0.01, output);
cv::imshow("out",output);
if (cv::waitKey(delay)>=0)
stop= true;
}
}