DocumentCode :
782967
Title :
3d object retrieval approach based on directed acyclic graph lightfield feature
Author :
Xiao, Q.K. ; Dai, Q.H. ; Wang, H.Y.
Author_Institution :
Autom. Dept., Tsinghua Univ., Beijing
Volume :
44
Issue :
14
fYear :
2008
Firstpage :
847
Lastpage :
848
Abstract :
A new 3D object retrieval methodology is proposed by exploiting a novel directed acyclic graph lightfield feature (DLF), in which the so-called lightfield is made up of around 2000-5000 colour views. The descriptor overcomes the disadvantages of the existing view-based 3D object retrieval methods. Benefiting from shock graph and Bayesian network learning, this DLF is simple, accurate and noise robust as compared to existing methods. Results of experiments show that the proposed method is superior to others.
Keywords :
belief networks; content-based retrieval; learning (artificial intelligence); solid modelling; video retrieval; 3D video object retrieval; Bayesian network learning; content-based retrieval; directed acyclic graph lightfield feature; shock graph;
fLanguage :
English
Journal_Title :
Electronics Letters
Publisher :
iet
ISSN :
0013-5194
Type :
jour
DOI :
10.1049/el:20080314
Filename :
4558443
Link To Document :
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