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Proceedings Paper

Salient local 3D features for 3D shape retrieval
Author(s): Afzal Godil; Asim Imdad Wagan
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Paper Abstract

In this paper we describe a new formulation for the 3D salient local features based on the voxel grid inspired by the Scale Invariant Feature Transform (SIFT). We use it to identify the salient keypoints (invariant points) on a 3D voxelized model and calculate invariant 3D local feature descriptors at these keypoints. We then use the bag of words approach on the 3D local features to represent the 3D models for shape retrieval. The advantages of the method are that it can be applied to rigid as well as to articulated and deformable 3D models. Finally, this approach is applied for 3D Shape Retrieval on the McGill articulated shape benchmark and then the retrieval results are presented and compared to other methods.

Paper Details

Date Published: 27 January 2011
PDF: 8 pages
Proc. SPIE 7864, Three-Dimensional Imaging, Interaction, and Measurement, 78640S (27 January 2011); doi: 10.1117/12.872984
Show Author Affiliations
Afzal Godil, National Institute of Standards and Technology (United States)
Asim Imdad Wagan, Quest Univ. (Pakistan)


Published in SPIE Proceedings Vol. 7864:
Three-Dimensional Imaging, Interaction, and Measurement
J. Angelo Beraldin; Ian E. McDowall; Atilla M. Baskurt; Margaret Dolinsky; Geraldine S. Cheok; Michael B. McCarthy; Ulrich Neuschaefer-Rube, Editor(s)

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