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Traditional matrix factorization methods approximate high dimensional data with a low dimensional subspace. This imposes constraints on the matrix elements which allow for estimation of missing entries. A lower rank provides stronger constraints and makes estimation of the missing entries less ambiguous at the cost of measurement fit. In this paper we propose a new factorization model that further...
We propose a new approach that integrates object tracking with object segmentation in a closed loop. The EM-like algorithm for color-histogram-based object tracking is modified to deal with the appearance models of the object and background represented by the Gaussian mixture models which are more efficient in RGB color space. It provides a rough object spatial model to guide segmentation. A five-layer...
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