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View-based 3D model retrieval with probabilistic graph model

delete2010-06-01
delete37
PRE
AI
Y
Yue Gao
唐金辉 cover
唐金辉 (Jinhui Tang) *
H
Haojie Li
戴
戴琼海 (Qionghai Dai)
N
Naiyao Zhang
DOI:10.1016/j.neucom.2009.11.050delete
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Abstract

Abstract

En 中文
In this paper, we present a view-based 3D model retrieval algorithm using probabilistic graph model. In this work, five circle camera arrays are employed, and five groups of views are captured from each 3D model. Each captured view set is modeled as a first order Markov Chain. The task of 3D model retrieval is defined as a probabilistic analysis procedure, and the comparison between the query and other 3D models is changed to compute the conditional probabilities of 3D models in the database given the query model. The purpose to search 3D model is to find the maximal a posterior probability of the models in the database given the query model. Then, we present a solution to estimate the conditional probabilities. The proposed 3D model retrieval algorithm has been evaluated on the NTU 3D model database. Experimental results and comparison with other methods show the effectiveness of the proposed approach. Crown Copyright (C) 2010 Published by Elsevier B.V. All rights reserved.
Keywords:
3D model
Retrieval
Probabilistic graph model
View-based
Markov chain
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Journal

Neurocomputing cover
Neurocomputing
IF:
6.5
Papers:
2.5W
Citations:
6.5W

Organization

T
tsinghua university
Scholars:
11.9W
Papers: 10.0W
Citations: 137
D
Dalian University of Technology
Scholars:
6.0W
Papers: 4.4W
Citations: 5.5W
N
National University of Singapore
Scholars:
7.6W
Papers: 6.5W
Citations: 11.4W
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Vibration-based structural health monitoring using large sensor networks
err2010-04-25
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PREAI
errA. Deraemaeker; A. Preumont; E. Reynders; G. De Roeck; J. Kullaa; V. Lamsa; K. Worden; G. Manson; R. Barthorpe; E. Papatheou; P. Kudela; P. Malinowski; W. Ostachowicz; T. Wandowski
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