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Learning a discriminative classifier using shape context distances

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Learning a discriminative classifier using shape context distances
For purpose of object recognition, we learn one discriminative classifier based on one prototype, using shape context distances as the feature vector. From multiple prototypes, the outputs of the classifiers are combined using the method called "error correcting output codes". The overall classifier is tested on benchmark dataset and is shown to outperform existing methods with far fewer prototypes.
Hao Zhang 0003, Jitendra Malik
Added 12 Oct 2009
Updated 29 Oct 2009
Type Conference
Year 2003
Where CVPR
Authors Hao Zhang 0003, Jitendra Malik
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