A General Framework for Combining Visual Trackers - The "Black Boxes" Approach

Abstract. Over the past few years researchers have been investigating the enhancement of visual tracking performance by devising trackers that simultaneously make use of several different features. In this paper we investigate the combination of synchronous visual trackers that use different features while treating the trackers as "black boxes". That is, instead of fusing the usage of the different types of data as has been performed in previous work, the combination here is allowed to use only the trackers' output estimates, which may be modified before their propagation to the next time step. We propose a probabilistic framework for combining multiple synchronous trackers, where each separate tracker outputs a probability density function of the tracked state, sequentially for each image. The trackers may output either an explicit probability density function, or a sample-set of it via CONDENSATION. Unlike previous tracker combinations, the proposed framework is fairly...

• Type: Journal
• Year: 2006
• Where: IJCV
• Authors: Ido Leichter, Michael Lindenbaum, Ehud Rivlin
• Keywords: IJCV 2006, Probability Density Function, Separate Tracker, Synchronous Visual Trackers