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Object Recognition as Many-to-Many Feature Matching
2006
International Journal of Computer Vision
Object recognition can be formulated as matching image features to model features. When recognition is exemplar-based, feature correspondence is one-to-one. However, segmentation errors, articulation, scale difference, and within-class deformation can yield image and model features which don't match one-to-one but rather many-tomany. Adopting a graph-based representation of a set of features, we present a matching algorithm that establishes many-to-many correspondences between the nodes of two
doi:10.1007/s11263-006-6993-y
fatcat:35o2peidqbcoxo7tfnciluu7lm