- Kernel codebooks for scene categorization
- Lecture Notes in Computer Science
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- Faculty of Science (FNWI)
- Informatics Institute (IVI)
This paper introduces a method for scene categorization by modeling ambiguity in the popular codebook approach. The codebook approach describes an image as a bag of discrete visual codewords, where the frequency distributions of these words are used for image categorization. There are two drawbacks to the traditional codebook model: codeword uncertainty and codeword plausibility. Both of these drawbacks stem from the hard assignment of visual features to a single codeword. We show that allowing a degree of ambiguity in assigning codewords improves categorization performance for three state-of-the-art datasets.
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Proceedings title: Computer Vision - ECCV 2008: 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008: Proceedings, Part III
Place of publication: Berlin
Editors: D. Forsyth, P. Torr, A. Zisserman
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