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Learning a discriminative classifier using shape context distances
Madison, Wisconsin June 18-June 20
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2003.12113602003 IEEE Computer Society Conference ...
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Hao Zhang, University of California at Berkeley
Jitendra Malik, University of California at Berkeley
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.
Citation:
Hao Zhang, Jitendra Malik, "Learning a discriminative classifier using shape context distances," cvpr, vol. 1, pp.242, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '03) - Volume 1, 2003
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