Fast motion estimation using spatio-temporal correlations

  • Authors:

  • Hyo Sun Yoon;Jae Myeong Yoo;Toan Nguyen Dinh;Hwa Jeong Son;Mi Seon Park;Guee Sang Lee

  • Affiliations:

  • Department of Computer Science, Chonnam National University, Kwangju, Korea;Department of Computer Science, Chonnam National University, Kwangju, Korea;Department of Computer Science, Chonnam National University, Kwangju, Korea;Department of Computer Science, Chonnam National University, Kwangju, Korea;Department of Computer Science, Chonnam National University, Kwangju, Korea;Department of Computer Science, Chonnam National University, Kwangju, Korea

  • Venue:
  • ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
  • Year:
  • 2006

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Abstract

Motion Estimation (ME) is an important part of video encoding systems, since it can significantly affect the output quality of an encoded sequences. However, ME requires a significant part of the encoding time, because ME is a combination of techniques such as motion starting point, motion search pattern, etc. For this reason, low complexity motion estimation algorithms are viable solutions. In this paper, we propose a motion estimation algorithm to find the most accurate motion vectors(MVs) with the aim to maximize the encoding speed as well as the image quality. The proposed algorithm takes advantage of spatio-temporal correlations to decide the search pattern and the search start point adaptively and to avoid unnecessary motion vector search. Experiments show that the speedup improvement of the proposed algorithm over Motion Vector Field Adaptive Search Technique (MVFAST) and Predictive Motion Vector Fiekd Adaptive Search Technique (PMVFAST) can be up to 1.5 ~ 8 times faster while maintaining very similar image quality.