Video segmentation based on adaptive combination of multiple features according to MPEG-4

Video segmentation for object based video coding according to MPEG-4 should be able to segment interested objects in video sequence clearly. This paper presents the object segmentation algorithm which image features are combined to use in segmentation process following to characteristic of video signal. Because the combination of many features in video sequence is a method that can achieve high quality object segmentation. In addition, this algorithm is an adaptive method that many parameters can be adjusted in order to give clearly segmentation. The significant features are used in segmentation process including color, motion vector and change information. A fast shortest spanning tree (SST) algorithm is adapted to use for fast segmenting image boundary. Motion vectors are estimated and searched by thresholding hierarchical block matching (HBM) which want quite low computation and give a few groups of motion vectors. The change information is used to detect moving objects that can separate between moving object and static background. After that, each feature will be considered in segmentation decision process to segment interested objects. Then the post processing refines the final segmentation. The results from many test sequences have good quality and show object boundary clearly.