Abstract
A novel light weight background subtraction algorithm proposed in this letter addresses the issue of executing real time motion detection in fog computing, which is a resource constrained environment. The proposed algorithm compresses the original high dimensional video frame into low dimensional space using random projection (RP) and the motion detection is identified using the structural similarity (SSIM) index. The objective of the proposed algorithm is to select the frames with motion and discard the remaining frame in order to reduce the storage and computational cost for the cloud users. The proposed algorithm is evaluated using CDNET 2014 video data and the results are verified in terms of selected frames per video(SFPV), percentage of reduction (POR) and running time. From the experiment, it is evident that the proposed algorithm reduces nearly 67 percent of storage cost with trifling computational expense.
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