DocumentCode :
2446127
Title :
Parallel Global Optimal Approach of Feedback for 3D CAD Model Retrieval
Author :
Hu, Baokun ; Liu, Yusheng ; Gao, Shuming
Author_Institution :
Zhejiang Univ., Hangzhou
fYear :
2007
fDate :
15-18 Oct. 2007
Firstpage :
132
Lastpage :
137
Abstract :
A parallel global optimal approach of feedback is proposed for 3D CAD model retrieval in this study. First, a novel unified mathematical model with multi-object for similarity field modification based relevance feedback is brought forward and the simplification is also given. Second, a new algorithm based on particle swarm optimization is proposed to optimize above model. In this algorithm, the particle can fly under the guide of its experience and a leader queue helps to avoid immature convergence. At last, an implementation is given and the results show that better feedback results are obtained for CAD model retrieval with the proposed method.
Keywords :
CAD; image retrieval; particle swarm optimisation; relevance feedback; 3D CAD model retrieval; parallel global optimal approach; particle swarm optimization; similarity field modification based relevance feedback; Bayesian methods; Convergence; Electronic mail; Feedback; Gaussian distribution; Mathematical model; Particle swarm optimization; Radio frequency; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Aided Design and Computer Graphics, 2007 10th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1579-3
Electronic_ISBN :
978-1-4244-1579-3
Type :
conf
DOI :
10.1109/CADCG.2007.4407869
Filename :
4407869
Link To Document :
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