Deformable shape retrieval using bag-of-feature techniques

Hedi Tabia; Mohamed Daoudi; Jean-Philippe Vandeborre; Olivier Colot

doi:10.1117/12.872182

27 January 2011 Deformable shape retrieval using bag-of-feature techniques

Hedi Tabia, Mohamed Daoudi, Jean-Philippe Vandeborre, Olivier Colot

Proceedings Volume 7864, Three-Dimensional Imaging, Interaction, and Measurement; 78640P (2011) https://doi.org/10.1117/12.872182
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

We present a novel method for 3D-shape matching using Bag-of-Feature techniques (BoF). The method starts by selecting and then describing a set of points from the 3D-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 BoF histogram counting the occurrences of every word is computed. These results clearly demonstrate that the method is robust to non-rigid 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.

Citation Download Citation

Hedi Tabia, Mohamed Daoudi, Jean-Philippe Vandeborre, and Olivier Colot "Deformable shape retrieval using bag-of-feature techniques", Proc. SPIE 7864, Three-Dimensional Imaging, Interaction, and Measurement, 78640P (27 January 2011); https://doi.org/10.1117/12.872182

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