Color invariant SURF in discriminative object tracking
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part II
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Visual tracking is a fundamental task in computer vision. However there has been no systematic way of analyzing visual trackers so far. In this paper we propose a method that can help researchers determine strengths and weaknesses of any visual tracker. To this end, we consider visual tracking as an isolated problem and decompose it into fundamental and independent subproblems. Each subproblem is designed to associate with a different tracking circumstance. By evaluating a visual tracker onto a specific subproblem, we can determine how good it is with respect to that dimension. In total we come up with thirteen subproblems in our decomposition. We demonstrate the use of our proposed method by analyzing working conditions of two state-of-theart trackers.