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Proceedings Paper

Fast motion prediction algorithm for multiview video coding
Author(s): Abdelrahman Abdelazim; Guang Y. Zhang; Stephen James Mein; Martin Roy Varley; Djamel Ait-Boudaoud
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Paper Abstract

Multiview Video Coding (MVC) is an extension to the H.264/MPEG-4 AVC video compression standard developed with joint efforts by MPEG/VCEG to enable efficient encoding of sequences captured simultaneously from multiple cameras using a single video stream. Therefore the design is aimed at exploiting inter-view dependencies in addition to reducing temporal redundancies. However, this further increases the overall encoding complexity In this paper, the high correlation between a macroblock and its enclosed partitions is utilised to estimate motion homogeneity, and based on the result inter-view prediction is selectively enabled or disabled. Moreover, if the MVC is divided into three layers in terms of motion prediction; the first being the full and sub-pixel motion search, the second being the mode selection process and the third being repetition of the first and second for inter-view prediction, the proposed algorithm significantly reduces the complexity in the three layers. To assess the proposed algorithm, a comprehensive set of experiments were conducted. The results show that the proposed algorithm significantly reduces the motion estimation time whilst maintaining similar Rate Distortion performance, when compared to both the H.264/MVC reference software and recently reported work.

Paper Details

Date Published: 3 June 2011
PDF: 6 pages
Proc. SPIE 8056, Visual Information Processing XX, 80560K (3 June 2011); doi: 10.1117/12.886980
Show Author Affiliations
Abdelrahman Abdelazim, Univ. of Central Lancashire (United Kingdom)
Guang Y. Zhang, Univ. of Central Lancashire (United Kingdom)
Stephen James Mein, Univ. of Central Lancashire (United Kingdom)
Martin Roy Varley, Univ. of Central Lancashire (United Kingdom)
Djamel Ait-Boudaoud, Univ. of Portsmouth (United Kingdom)

Published in SPIE Proceedings Vol. 8056:
Visual Information Processing XX
Zia-ur Rahman; Stephen E. Reichenbach; Mark Allen Neifeld, Editor(s)

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