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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.9 P.1500~1507

http://doi.org/10.1631/jzus.2006.A1500


Multi-level spherical moments based 3D model retrieval


Author(s):  LIU Wei, HE Yuan-jun

Affiliation(s):  Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Corresponding email(s):   liu-wei@sjtu.edu.cn

Key Words:  3D model retrieval, Spherical moments, Feature extraction, Pose normalization


LIU Wei, HE Yuan-jun. Multi-level spherical moments based 3D model retrieval[J]. Journal of Zhejiang University Science A, 2006, 7(9): 1500~1507.

@article{title="Multi-level spherical moments based 3D model retrieval",
author="LIU Wei, HE Yuan-jun",
journal="Journal of Zhejiang University Science A",
volume="7",
number="9",
pages="1500~1507",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A1500"
}

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%T Multi-level spherical moments based 3D model retrieval
%A LIU Wei
%A HE Yuan-jun
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%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A1500

TY - JOUR
T1 - Multi-level spherical moments based 3D model retrieval
A1 - LIU Wei
A1 - HE Yuan-jun
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 9
SP - 1500
EP - 1507
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.A1500


Abstract: 
In this paper a novel 3D model retrieval method that employs multi-level spherical moment analysis and relies on voxelization and spherical mapping of the 3D models is proposed. For a given polygon-soup 3D model, first a pose normalization step is done to align the model into a canonical coordinate frame so as to define the shape representation with respect to this orientation. Afterward we rasterize its exterior surface into cubical voxel grids, then a series of homocentric spheres with their center superposing the center of the voxel grids cut the voxel grids into several spherical images. Finally moments belonging to each sphere are computed and the moments of all spheres constitute the descriptor of the model. Experiments showed that Euclidean distance based on this kind of feature vector can distinguish different 3D models well and that the 3D model retrieval system based on this arithmetic yields satisfactory performance.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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