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Object categorization using co-occurrence, location and appearance
2008
2008 IEEE Conference on Computer Vision and Pattern Recognition
In this work we introduce a novel approach to object categorization that incorporates two types of context -cooccurrence and relative location -with local appearancebased features. Our approach, named CoLA (for Cooccurrence, Location and Appearance), uses a conditional random field (CRF) to maximize object label agreement according to both semantic and spatial relevance. We model relative location between objects using simple pairwise features. By vector quantizing this feature space, we learn
doi:10.1109/cvpr.2008.4587799
dblp:conf/cvpr/GalleguillosRB08
fatcat:77eaoqqbbrbbnkuwjju3mcxh6e