Finding similar and discriminative parts of deformable shape classes

This paper presents a novel representation and matching method for deformable shapes. The proposed approach finds most expressive segments of a deformable shape category called similar and discriminative parts, which is able to distinguish the learned shape class from other groups. And it leads a learning strategy together with a matching algorithm. Then we test our method with MPEG-7 data set.

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