Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/64726
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Type: Conference paper
Title: Retrieving 3D CAD models using 2D images with optimized weights
Author: Li, L.
Wang, H.
Chin, T.J.
Suter, D.
Zhang, S.
Citation: Proceedings, 2010 3rd International Congress on Image and Signal Processing : CISP 2010, vol. 4 / Zheng-Hua Tan, Yi Wan, Tao Xiang & Yibin Song (eds.): pp. 1586-1589
Publisher: IEEE
Publisher Place: USA
Issue Date: 2010
ISBN: 9781424465163
Conference Name: International Congress on Image and Signal Processing (3rd : 2010 : Yantai, China)
Statement of
Responsibility: 
Liang Li, Hanzi Wang, Tat-Jun Chin, David Suter, Shusheng Zhang
Abstract: An effective method for retrieving 3D models is to represent and discriminate them with their 2D images projected from multiple viewpoints. Such view-based methods conform more closely to human visual recognition for 3D model retrieval, since the human retina essentially captures 2D images. However, most of the existing view-based methods do not take into account that different views have different importance even though they belong to the same object. To address this problem, we propose a novel view-based method for 3D CAD model retrieval. First, the PHOG descriptor is employed to describe the 2D images projected from a model. Then, Lagrange multipliers, vector quantization and a Support Vector Machine (SVM) are used to adaptively assign an optimal weight to each projected image. The similarity between a 3D query model and a 3D object in database is determined by the likeness of their corresponding 2D images associated with optimal weights. The effectiveness of the proposed method is shown in the experimental part.
Keywords: Content-based 3D model retrieval; Lagrange mulitpliers; PHOG; SVM; vector quantization
Rights: ©2010 IEEE
RMID: 0020105450
DOI: 10.1109/CISP.2010.5646952
Appears in Collections:Computer Science publications

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