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Technical Program
Paper Detail
| Paper: | WA-L5.7 |
| Session: | Block Matching-Based Motion Estimation |
| Time: | Wednesday, October 11, 12:00 - 12:20 |
| Presentation: |
Lecture
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| Title: |
MULTI-PATH SEARCH ALGORITHM FOR BLOCK-BASED MOTION ESTIMATION |
| Authors: |
Sumeer Goel; University of Lousiana at Lafayette | | | | | Magdy Bayoumi; University of Lousiana at Lafayette | | |
| Abstract: |
Block-based motion estimation algorithms are widely adopted by video coding standards due to their simplicity and good distortion performance. Amongst these, pattern based search algorithms are very popular. The basic assumption made by these algorithms is that there exists a unimodal error surface within the search window. As seen in real world video sequences, this is far from reality and the algorithms often get stuck in local minimums yielding sub-optimal results. We propose a multi-path search (MPS) algorithm that utilizes more than one path to find the absolute minima. Wrong search paths are avoided early resulting in faster search. Better motion vectors are estimated increasing the video quality, consequently reducing the bitrate requirement. MPS algorithm offers flexibility and robustness with better speed and quality. Results show that a speedup of upto 34% is achieved with slight increase in PSNR as compared to its best competitor. When compared to full search, the proposed algorithm looses only 0.1%~2% in PSNR while saving 92%~95% computations. |
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