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In this correspondence, our goal is to develop a visual tracking algorithm that is able to track moving objects in the presence of illumination variations in the scene and that is robust to occlusions. We treat the illumination and motion ( translation and scale) parameters as the unknown “state” sequence. The observation is the entire image, and the observation model allows for occasional...
In recent work, the authors introduced a multiplicative, low dimensional model of illumination that is computed as a linear combination of a set of simple-to-compute Legendre basis functions. The basis coefficients describing illumination change, are can be combined with the "shape" vector to define a joint `shape"-illumination space for tracking. The increased dimensionality of the...
In this paper we introduce a multiplicative, low dimensional model for appearance change in the context of visual tracking. The model is defined by a linear combination of smoothly changing basis functions. Secondly, we show that a small number of cluster centers in this new space can be used to represent the illumination conditions existing in the scene. These cluster centers can be learned from...
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