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This paper presents a new visual tracking framework based on an adaptive color attention tuned local sparse model. The histograms of sparse coefficients of all patches in an object are pooled together according to their spatial distribution. A particle filter methodology is used as the location model to predict candidates for object verification during tracking. Since color is an important visual...
A new color attention preserved sparse generative object model is proposed to handle occlusion and illumination variations in the visual tracking task. The color attention is represented by the fast calculated color descriptor on color names, which is used to weight the similarity measurement of the sparse generative model. In the sparse generative model, the image region of the object is divided...
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