Moving object segmentation in the h.264 compressed domain

Authors:
Changfeng Niu;Yushu Liu
Affiliations:
School of Computer Science and Technology, Beijing Institute of Technology, Beijing, P.R. China;School of Computer Science and Technology, Beijing Institute of Technology, Beijing, P.R. China
Venue:
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Year:
2009

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Abstract

A novel method for moving object segmentation in the H.264 compressed domain is proposed. In contrast to all known methods in which only motion information is used, the proposed method utilizes some characters of H.264 besides motion information with no more decoding required. In the proposed method, motion vector is refined firstly by spatial and temporal correlation of motion and initial segmentation is produced by using the motion vector difference after global motion estimation. Then, the result of segment-ation is refined by using intra prediction information in intra-frame. The refined result of segmentation is projected to subsequent frame and expansion and contraction operation is followed. Experimental results for several H.264 compressed video sequences demonstrate the good segmentation quality of the proposed approach.