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1 . For this lab you are going to implement a background subtraction solution for the included video clip. 2 . Since we ve been

1. For this lab you are going to implement a background subtraction solution for the included video
clip.
2. Since weve been mainly working with images up to this point, well keep things simple and
break down our video into several images. Recall that a video is really a sequence of images that
are rapidly displayed one after another. The following matlab code will break your video into
multiple image files:
mov = VideoReader('YourVideoFileName.wmv');
for i=1:mov.NumberOfFrames
img = read(mov,i);
bwImage = rgb2gray(img);
outputFileName = sprintf('bwImage%d.jpg',i);
imwrite(bwImage, outputFileName, 'jpg');
end
3. You will want to run the above code only once on your video file. This step is typically called
preprocessing.
4. There are several different methods available for background subtraction, and were going to
focus on a basic approach. A basic approach is to track the last 10 pixel values of each video
frame. If the intensity of the pixel changes either brighter or darker by a set threshold, we will
flag this pixel as a foreground pixel. In order to do this, you will need to know the dimensions of
the video you will be using and create a matrix of those dimensions with a third dimension of
value 10. For example, if the video you are using is 1920x1080, you will want to create a matrix
of size 1920x1080x10. A matrix of this size will allow us to keep track of the last 10 values for
each pixel.
5. If youre not sure on the size of your video, you can read in one of the image files and check its
dimensions:
myTest = imread('bwImage1.jpg');
size(myTest)
ans =
10801920
6. The image above is 1920 by 1080, but Matlab flips the horizontal and vertical so it displays it as
shown above.
7. Read in the first 10 frames to create a matrix that you will track the last 10 frames viewed. This
matrix will be used to calculate the average value at each pixel location.
8. What you want to do next is create a loop that will run through each of the image files that you
created. In each of these iterations you will want to do the following:
a. Compare each of the pixel values (height by width) to the average value stored in the
average matrix. If the absolute value of the difference is greater than some threshold
(start with threshold =20) set the value of that correspond pixel in the newImage to be
white (intensity value 255). If its less than the threshold you will set the value of that
corresponding pixel in the newImage to be black (intensity value 0). If the pixel value is
white, it is a foreground pixel, if its set to black, its a background pixel.
b. Update the average matrix by replacing the oldest image in the matrix with the current
image.
9. When youve created a new set of images, youll want to combine them back together again
(Please note you must first create a directory called modifiedImages).
mov = VideoReader('baseball.mp4');
totalImages =360;
videoFrameRate = mov.FrameRate;
videoHeight = mov.Height;
videoWidth = mov.Width;
outputVideo = VideoWriter('myfile.avi');
outputVideo.FrameRate = videoFrameRate;
open(outputVideo);
for i=11:totalImages
outputFileName = sprintf('modifiedImages\\bwImage%d.jpg', i);
myImage = imread(outputFileName);
writeVideo(outputVideo, myImage);
end
close(outputVideo)

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