In video post-production it is often necessary to track interest points in the video. This is called off-line tracking, because the complete video is available to the algorithm and can be contrasted with on-line tracking, where an incoming stream is tracked in real time. Off-line tracking should be accurate and â€“ if used interactively â€“ needs to be fast, preferably faster than real-time. We describe a 50 to 100 frames per second off-line tracking algorithm, which globally maximizes the probability of the track given the complete video. The algorithm is more reliable than previous methods because it explains the complete frames, not only the patches of the ?nal track, making as much use of the data as possible. It achieves ef?ciency by using a greedy search strategy with deferred cost evaluation, focusing the computational effort on the most promising track candidates while ?nding the globally optimal track.

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