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Recent years have seen a sharp rise in shape classification applications, and following suit, several frameworks have been proposed for efficient indexing of shape models. Here we propose a state-of-the-art shape matching framework which concomitantly provides transformation invariance and computationally efficient querying. Shapes are represented as probability density functions estimated on the...
Driven by desirable attributes such as topological characterization and invariance to isometric transformations, the use of the Laplace-Beltrami operator (LBO) and its associated spectrum have been widely adopted among the shape analysis community. Here we demonstrate a novel use of the LBO for shape matching and retrieval by estimating probability densities on its Eigen space, and subsequently using...
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