DocumentCode :
2876336
Title :
3D Model Retrieval Method Based on Single View
Author :
Zhi Liu ; Qihua Chen ; Xiang Pan ; Yipan Feng
Author_Institution :
Coll. of Comput. Sci. & Technol., Zhejiang Univ. of Technol., Hangzhou, China
fYear :
2012
fDate :
17-18 Nov. 2012
Firstpage :
275
Lastpage :
279
Abstract :
In order to solve the view redundant problem in existing research work, we propose an approach based on a single view for 3D model shape feature measuring, and the similarity between models is calculated through dynamic programming algorithm. This method implements single view feature description and shape matching for 3D model. The algorithm is composed of three steps: Firstly, the pose of a 3D model is adjusted and the main view of the 3D model that best describes the profile features of the 3D model can be acquired by rendering. Then, through contour sampling of the rendered view, the model shape feature is described through extracting inner distance and inner angle. Finally, the similarity between different 3D models is calculated through dynamic programming algorithm. The experimental results show that the retrieval precision of the proposed method based on a single view is better than some traditional retrieval methods using 3D shape feature descriptor.
Keywords :
dynamic programming; feature extraction; image retrieval; rendering (computer graphics); solid modelling; 3D model pose adjustment; 3D model retrieval method; 3D model shape feature measurement; contour sampling; dynamic programming algorithm; feature description; inner angle extraction; inner distance extraction; model similarity; profile feature; rendering; retrieval precision; shape matching; view redundant problem; Computational modeling; Feature extraction; Gravity; Histograms; Robustness; Shape; Solid modeling; 2D contour; 3D model retrieval; similarity measuring; single view;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security (CIS), 2012 Eighth International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-4725-9
Type :
conf
DOI :
10.1109/CIS.2012.68
Filename :
6405843
Link To Document :
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