Moving object detection using spatial coherence
Kyungnam Kim · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
Moving object detection from videos is one of important problems in intelligent video surveillance. Our goal is to extract moving foreground objects from the background of a scene captured from a stationary camera. We propose methods to improve a background subtraction (BGS) algorithm effectively using the spatial coherence of foreground regions - spatial filtering and region-based BGS. The proposed spatial filtering is based on the spatial coherence around the pixel neighborhood. In the region-based BGS, pixel deviation values (from the background model) are aggregated in a region for region-wise detection. We demonstrate the improved performance using the proposed methods on several indoor/outdoor video sequences.