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|Title:||Retrieving 3D CAD models using 2D images with optimized weights|
|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|
|Conference Name:||International Congress on Image and Signal Processing (3rd : 2010 : Yantai, China)|
|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|
|Appears in Collections:||Computer Science publications|
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