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18th December 2016, 02:08 | #21 | Link |
Professional Lemming
Join Date: Dec 2003
Location: Stuttgart, Germany
Posts: 359
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Motion Estimation Heuristics
[QUOTE=LigH;1789870
Star has a smaller scope right away, it will terminate faster for rather regular motion, which may differ a bit more in mostly vertical or horizontal direction. The scope of UMH is wider, there are already 49 samples always in a first step (16 directions * 3 radii + the origin of the estimation), which will make it probably one of the slowest of these three on the average, yet may be more suitable for the case of a rather shaky camera or otherwise randomly changing motion. And SEA is effectively exhaustive over the whole motion range square, its speed would be constantly high, equal to the dual logarithm of the range for 8..9 samples in each refinement step; to beat UMH on average speed, it has to calculate at most 6 steps which would cover a square of +/- 32 pixels around the estimation, if I'm not completely wrong... [/QUOTE] I'm a bit out of touch with the latest progress in this matter. Has anyone thought about a way to adaptively trade off effort and quality of the ME method in use? Maybe evaluating several methods on a small subset of blocks and comparing the effort and residue? It would be possible to adaptively select the appropriate ME method for a given context. A secondary trade-off is present between reaction time to changed context and overhead of ME re-evaluation.
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