Better computer vision under video compression, an example using mean shift tracking

In this paper, our goal is to understand what needs to be done to enable computer vision algorithms running on uncompressed image sequences to run as well on image sequences that have undergone compression and then decompression. The central conflict of context based computer vision algorithms versus the structured block based approach of today´s codecs means that more has to be done than to simply create a divide between coding foreground preferentially and giving less importance to background. We take as example, a single computer vision algorithm, the mean shift tracker and see that its performance can be improved substantially in low bit rate scenarios, albeit some tradeoffs.