| 摘要 |
Some embodiments include a video copy detection approach based on speeded up robust features (SURF) trajectory building, local sensitive hash (LSH) indexing, and spatial-temporal-scale registration. First, interesting points' trajectories are extracted by SURF. Next, an efficient voting based spatial-temporal-scale registration approach is applied to estimate the optimal transformation parameters (shift and scale) and achieve the final video copy detection results by propagations of video segments in both spatial-temporal and scale directions. To speed up the detection speed, local sensitive hash (LSH) indexing is used to index trajectories for fast queries of candidate trajectories.
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