Paper Info
Title
Shape-based retrieval and analysis of 3D models using fuzzy weighted symmetrical depth images
Abstract
With the rapid development of 3D scanners, graphic accelerated hardware and 3D modeling tools, the application of 3D model databases is growing in both numbers and sizes, e.g. 3D body scans, head model and virtual mannequins. There is a pressing need for effective content-based 3D model retrieval methods. In this paper, a novel 3D model retrieval approach is proposed by using the Fuzzy Weighted Symmetrical Depth Images (FW-SDI). Firstly, three symmetrical planes of the 3D model are obtained based upon principal plane analysis and sequential quadratic programming, which are the distinctive characteristics of 3D model and perpendicular to each other. Secondly, three novel depth Images (NDI) and three depth differential images (DDI) are extracted by projecting the 3D surface to the proposed symmetrical planes. The Fourier descriptors of the novel depth Images and depth differential images are calculated. Finally, a fuzzy weighted procedure is conducted for combining the Fourier descriptors of NDI and DDI. Experiment results show that the proposed method can achieve better retrieval performance than others.
Year
DOI
Venue
2012
10.1016/j.neucom.2012.02.027
Neurocomputing
Keywords
DocType
Volume
fuzzy weighted symmetrical depth,shape-based retrieval,better retrieval performance,head model,depth differential image,model retrieval method,model retrieval approach,model databases,fourier descriptors,novel depth images,proposed symmetrical plane,sequential quadratic programming
Journal
89,
ISSN
Citations 
PageRank 
0925-2312
4
0.42
References 
Authors
33
6
Name
Order
Citations
PageRank
Kuan-Sheng Zou1152.28
Chee-Kooi Chan240.75
Si-Xiang Peng340.42
Ameersing Luximon4317.14
Zeng-Qiang Chen555072.38
Wai-Hung Ip61299.58