Segmentation of moving pedestrians within the compressed domain

Video encoding standards, namely MPEG-2, store large amounts of information obtained for compression purposes that can be accessed with minimal decoding. This paper shows that, with proper filtering of motion vectors and DCT coefficients, accurate segmentation results can be achieved by combining both reliable motion estimation and background subtraction. We further present a fine segmentation step that exploits specific blob characteristics to reduce segmentation noise and solve some occlusion problems. Examples using real videos from underground station CCTV cameras show that compressed domain information can be the key for successful surveillance applications where very fast algorithms with high accuracy are required.