DocumentCode :
1898358
Title :
Research on Semantic-Based 3D Model Retrieval
Author :
Peng, Shan ; Li, Haisheng ; Liu, Xuan ; Cai, Qiang
Author_Institution :
Coll. of Comput. & Inf. Eng., Beijing Technol. & Bus. Univ., Beijing, China
Volume :
2
fYear :
2012
fDate :
23-25 March 2012
Firstpage :
235
Lastpage :
238
Abstract :
In this paper, we present on the research of semantic-based 3D model retrieval system and its developed framework. We use RDF annotation to label 3D models for improving retrieval precision. The framework contains three parts: preprocessing, feature extraction and similarity measurement. The parts are recommended to analyze the 3D model. In the preprocessing part, we deploy PCA to make models normalization. In the feature extraction part, shape component and semantic component are used to construct an efficient 3D object retrieval scheme. In the last, similarity measurements, like Euclidean distance and quadratic form distance, compute the similarity distance between models. The developed framework is designed to improve the efficiency of 3D model retrieval system.
Keywords :
feature extraction; image retrieval; principal component analysis; solid modelling; Euclidean distance; PCA; RDF annotation; feature extraction; quadratic form distance; semantic-based 3D model retrieval; similarity measurement; Computational modeling; Feature extraction; Resource description framework; Semantics; Shape; Solid modeling; Three dimensional displays; 3D model retrieval system; semantic-based; similarity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-0689-8
Type :
conf
DOI :
10.1109/ICCSEE.2012.356
Filename :
6188009
Link To Document :
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