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In this paper we introduce a novel framework for image classification using local visual descriptors ¨C group fusion sparse representation (GFSR), which casts the classification problem as a linear regression model with sparse constraints of the regression coefficients. Considering the intrinsic discriminative property of prior class label information, and the requirement of local consistency within...
Multimedia content analysis and management are a promising and challenging theme. In this paper we develop a novel approach to image representation, which we call group sparse representation (GSR), for image classification and video retrieval. The basic idea is to represent a test image as a weighted combination of all the training images. In particular, we introduce two sets of weight coefficients,...
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