Mutual information for enhanced feature selection in visual tracking

Victor Stamatescu; Sebastien Wong; David Kearney; Ivan Lee; Anthony Milton

doi:10.1117/12.2176556

14 May 2015 Mutual information for enhanced feature selection in visual tracking

Victor Stamatescu, Sebastien Wong, David Kearney, Ivan Lee, Anthony Milton

Proceedings Volume 9476, Automatic Target Recognition XXV; 947603 (2015) https://doi.org/10.1117/12.2176556
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

In this paper we investigate the problem of fusing a set of features for a discriminative visual tracking algorithm, where good features are those that best discriminate an object from the local background. Using a principled Mutual Information approach, we introduce a novel online feature selection algorithm that preserves discriminative features while reducing redundant information. Applying this algorithm to a discriminative visual tracking system, we experimentally demonstrate improved tracking performance on standard data sets.

Citation Download Citation

Victor Stamatescu, Sebastien Wong, David Kearney, Ivan Lee, and Anthony Milton "Mutual information for enhanced feature selection in visual tracking", Proc. SPIE 9476, Automatic Target Recognition XXV, 947603 (14 May 2015); https://doi.org/10.1117/12.2176556

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