Particle Swarm Clustering-Based Moving Object Segmentation in the H.264 Compressed Domain

Abstract

An approach of the moving object segmentation is proposed in this paper. Firstly the motion fields are extracted from the compressed stream, where the noise and the unreal motion blocks are removed by vector median filter. Then the motion vectors are accumulated by motion estimation, in order to get denser and prominent motion vectors. Finally the moving objects are segmented adaptively by particle swarm clustering algorithm. It is demonstrated by the experimental results that the moving objects in the compressed domain can be segmented effectively.