An improvement on an MCMC-based video tracking algorithm
This paper presents an approach to fully automatic people tracking in surveillance video recorded by stable camera. We propose an improvement on Benfold et al. tracking-by-detection algorithm . We extend the basic algorithm through filtering of person detector results and the scene entrance/exit positions construction. Moreover, the paper presents a modified method for tracklet position estimation. We compare several tracklet construction algorithms such as “Flock of Features” and normalized cross correlation. Our experiments reveal that all the proposed modifications improve both robustness and precision of tracks compared to the basic algorithm.
Keywordscomputer vision biometry video analytics
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