EFFICIENT BACK GROUND SUBTRACTION USING ADAPTIVE SGMM
Aiswarya Muralidharan · 2014
Background subtraction is one of the key techniques for automatic video analysis, especially in the domain of video surveillance because of their ability to cope with many challenging characteristic for surveillance systems in real time with low memory requirements. Background subtraction methods with respect to the challenges of video surveillance suffer from various shortcomings. To address this issue, first identify the main challenges of background subtraction. In this paper, we present a study of some relevant GMM approaches and analyze their underlying assumptions and design decisions. System is able to hold static foreground regions in the foreground, while correctly incorporating into the background model uncovered background regions.