Fast Multi-reference Motion Estimation via Enhanced Downhill Simplex Search

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Abstract

Block motion estimation can be regarded as a function minimization problem in a finite-dimensional space. Therefore, fast block motion estimation can be achieved by using an efficient function minimization algorithm instead of a predefined search pattern, such as diamond search. Downhill simplex search is an efficient derivative-free function minimization algorithm. In this paper, we proposed a fast block motion estimation algorithm based on applying the downhill simplex search for function minimization. Several enhanced schemes are proposed to improve the efficiency and accuracy, including a new initialization process, a special rounding scheme, and an early-stop error function evaluation procedure. We also extend the downhill simplex search for the multi-reference frame motion estimation problem. Experimental results show superior performance of the proposed algorithm over some existing fast block matching methods on several benchmarking video sequences.

Keywords

motion-estimation block-matching algorithm downhill simplex search multi-reference-frame motion estimation 

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Chen-Kuo Chiang
    • 1
  • Hwai-Chung Fei
    • 1
  • Shang-Hong Lai
    • 1
  1. 1.Department of Computer ScienceNational Tsing Hua UniversityHsinchuRepublic of China

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