Feature assisted search technique for motion estimation.

Content Provider	CiteSeerX
Author	Ra, Jong Beom Lee, Jae Hun
Abstract	Motion estimation (ME) is one of the most time-consuming parts in video encoding system, and significantly affects the quality of the reconstructed sequences. In this paper, we propose a new fast algorithm, or the Feature Assisted Search Technique for Motion Estimation (FASTME), which is a gradient descent search combined with a new search strategy, namely, one-dimensional feature matching based on selective integral projections (1DFM). 1DFM assists a local search around an initial search center with a low computational complexity. After performing 1DFM, a small diamond search pattern and more compact horizontal and vertical search patterns, are adaptively used according to the result of 1DFM. The proposed algorithm outperforms existing fast algorithms in terms of speed up performance. In addition, its PSNR performance is better or similar to those of existing fast algorithms.
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Access Restriction	Open
Subject Keyword	Compact Horizontal Fast Algorithm Time-consuming Part New Search Strategy Reconstructed Sequence Gradient Descent Search Vertical Search Pattern Search Technique Initial Search Center Small Diamond Search Pattern Low Computational Complexity Video Encoding System Selective Integral Projection Motion Estimation New Fast Algorithm Feature Assisted Search Technique One-dimensional Feature Psnr Performance Local Search
Content Type	Text