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Journal of Electronic Imaging

Three-dimensional object retrieval based on vector quantization of invariant descriptors
Author(s): Hedi Tabia; Olivier Colot; Mohamed Daoudi; Jean-Philippe Vandeborre
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Paper Abstract

A novel method for three-dimensional (3-D) shape retrieval using bag-of-feature techniques (BoF) is proposed. This method is based on vector quantization of invariant descriptors of 3-D object patches. Firstly, it starts by selecting and then describing a set of points from the 3-D object. Such descriptors have the advantage of being invariant to different transformations that a shape can undergo. Based on vector quantization, we cluster those descriptors to form a shape vocabulary. Then, each point selected in the object is associated to a cluster (word) in that vocabulary. Finally, a weighted vector counting the occurrences of every word is computed. These results clearly demonstrate that the method is robust to nonrigid and deformable shapes, in which the class of transformations may be very wide due to the capability of such shapes to bend and assume different forms.

Paper Details

Date Published: 21 May 2012
PDF: 9 pages
J. Electron. Imag. 21(2) 023011 doi: 10.1117/1.JEI.21.2.023011
Published in: Journal of Electronic Imaging Volume 21, Issue 2
Show Author Affiliations
Hedi Tabia, TELECOM Lille 1 (France)
Olivier Colot, Univ. des Sciences et Technologies de Lille (France)
Mohamed Daoudi, TELECOM Lille 1 (France)
Jean-Philippe Vandeborre, TELECOM Lille 1 (France)

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