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Adaptive appearance learning for visual object tracking
2011
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
This paper addresses online learning of reference object distribution in the context of two hybrid tracking schemes that combine the mean shift with local point feature correspondences, and the mean shift under the Bayesian framework, respectively. The reference object distribution is built up by a kernel-weighted color histogram. The main contributions of the proposed schemes includes: (a) an adaptive learning strategy that seeks to update the reference object distribution when the changes are
doi:10.1109/icassp.2011.5946678
dblp:conf/icassp/KhanG11
fatcat:h7t76ahvw5hqthzladizewssoa