Fast motion and disparity estimation for multiview video coding

Zhipin Deng, Kebin Jia, Yui Lam Chan, Chang Hong Fu, Wan Chi Siu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)


Multiview video involves a huge amount of data, and as such, efficiently encoding each view is a critical issue for its wider application. In this paper, a fast motion and disparity estimation algorithm is proposed, utilizing the close correlation between temporal and interview reference frames. First, a reliable predictor is found according to the correlation of motion and disparity vectors. Second, an iterative search process is carried out to find the optimal motion and disparity vectors. The proposed algorithm makes use of the prediction vector obtained in the previous motion estimation for the next disparity estimation and achieves both optimal motion and disparity vectors jointly. Experimental results demonstrate that the proposed algorithm can successfully save an average of 86% of computational time with a negligible quality drop when compared to the joint multiview video model (JMVM) full search algorithm. Furthermore, in comparison with the conventional simulcast coding, the proposed algorithm enhances the video quality and also greatly increases coding speed.
Original languageEnglish
Pages (from-to)571-579
Number of pages9
JournalFrontiers of Computer Science in China
Issue number4
Publication statusPublished - 30 Apr 2010


  • disparity estimation
  • H.264
  • joint multiview video model (JMVM)
  • motion estimation
  • multiview video coding (MVC)

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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