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Shape classification through structured learning of matching measures

Chen, Longbin; McAuley, Julian; Feris, Rogerio S.; Caetano, Tiberio; Turk, Matthew


Many traditional methods for shape classification involve establishing point correspondences between shapes to produce matching scores, which are in turn used as similarity measures for classification. Learning techniques have been applied only in the second stage of this process, after the matching scores have been obtained. In this paper, instead of simply taking for granted the scores obtained by matching and then learning a classifier, we learn the matching scores themselves so as to...[Show more]

CollectionsANU Research Publications
Date published: 2009
Type: Conference paper
Source: Proceeings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009)
DOI: 10.1109/CVPRW.2009.5206792


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01_Chen_Shape_classification_through_2009.pdf1.75 MBAdobe PDFThumbnail
02_Chen_Shape_classification_through_2009.pdf46.19 kBAdobe PDFThumbnail

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