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Image retrieval with relevance feedback: from heuristic weight adjustment to optimal learning methods
Huang, T.S.; Xiang Sean Zhou;
Image Processing, 2001. Proceedings. 2001 International Conference on
Volume 3,
7-10 Oct. 2001
Page(s):2
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5 vol.3
Abstract:
Various relevance feedback algorithms have been proposed in recent years in the area of content-based image retrieval. This paper gives a brief review and analysis on existing techniques-from early heuristic-based feature weighting schemes to recently proposed optimal learning algorithms. In addition, the kernel-based biased discriminant analysis (KBDA) is proposed to fit the unique nature of relevance feedback as a biased classification problem. As a novel variant of traditional discriminant analysis, the proposed algorithm provides a trade-off between discriminant transform and regression. The kernel form is derived to deal with non-linearity in an elegant way. Experimental results indicate that significant improvement in retrieval performance is achieved by the new scheme
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