Video background subtraction using semi-supervised robust matrix completion
We propose a factorized robust matrix completion (FRMC) algorithm with global motion compensation to solve the video background subtraction problem. The algorithm decomposes a sequence of video frames into the sum of a low rank background component and a sparse motion component. The algorithm alternates between the solution of each component following a Pareto curve trajectory for each subproblem. For videos with moving background, we utilize the motion vectors extracted from the coded video bitstream to compensate for the change in the camera perspective. Performance evaluations show that our approach is faster than state-of-the-art solvers and results in highly accurate motion segmentation.