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Skeleton-based canonical forms for non-rigid 3D shape retrieval

Pickup, David, Sun, Xianfang, Rosin, Paul L. and Martin, Ralph Robert 2016. Skeleton-based canonical forms for non-rigid 3D shape retrieval. Computational Visual Media 2 (3) , pp. 231-243. 10.1007/s41095-016-0045-5

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Abstract

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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: canonical forms; shape retrieval; skeletons; pose invariance
Additional Information: Pdf uploaded in accordance with publisher's policy at http://www.sherpa.ac.uk/romeo/issn/2096-0433/ (accessed 21/04/2016)
Publisher: Springer
ISSN: 2096-0433
Funders: EPSRC
Date of First Compliant Deposit: 15 April 2016
Date of Acceptance: 20 February 2016
Last Modified: 28 Jun 2019 11:28
URI: http://orca.cf.ac.uk/id/eprint/89013

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