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https://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. 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 |
DOI: | 10.1109/CISP.2010.5646952 |
Published version: | http://dx.doi.org/10.1109/cisp.2010.5646952 |
Appears in Collections: | Aurora harvest Computer Science publications |
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