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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Publisher: Springer
Languages: English
Types: Article
Subjects: QA75

Classified by OpenAIRE into

ACM Ref: ComputingMethodologies_COMPUTERGRAPHICS
The retrieval of non-rigid 3D shapes is an important task. A common technique is to simplify this problem to a rigid shape retrieval task by producing a bending invariant canonical form for each shape in the dataset to be searched. It is common for these techniques to attempt to ``unbend'' a shape by applying multidimensional scaling to the distances between points on the mesh, but this leads to unwanted local shape distortions. We instead perform the unbending on the skeleton of the mesh, and use this to drive the deformation of the mesh itself. This leads to a computational speed-up and less distortions of the local details of the shape. We compare our method against other canonical forms and our experiments show that our method achieves state-of-the-art retrieval accuracy in a recent canonical forms benchmark, and only a small drop in retrieval accuracy over state-of-the-art in a second recent benchmark, while being significantly faster.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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  • Discovered through pilot similarity algorithms. Send us your feedback.

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