文章基本信息

标题：Improving 3D Shape Retrieval Methods based on Bag-of Feature Approach by using Local Codebooks
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作者：El Wardani Dadi ; El Mostafa Daoudi ; Claude Tadonki 等
期刊名称：International Journal of Future Generation Communication and Networking
印刷版ISSN：2233-7857
出版年度：2012
卷号：5
期号：4
出版社：SERSC
摘要：Recent investigations illustrate that view-based methods, with pose normalization pre-processing get better performances in retrieving rigid models than other approaches and still the most popular and practical methods in the field of 3D shape retrieval [1, 2, 3, 4, 5]. In this paper we present an improvement of 3D shape retrieval methods based on bag-of features approach. These methods use this approach to integrate a set of features extracted from 2D views of the 3D objects using the SIFT (Scale Invariant Feature Transform [6]) algorithm into histograms using vector quantization which is based on a global visual codebook. In order to improve the retrieval performances, we propose to associate to each 3D object its local visual codebook instead of a unique global codebook. The experimental results obtained on the Princeton Shape Benchmark database [6], for the BF-SIFT method proposed by Ohbuchi, et al., [2] and CM-BOF proposed by Zhouhui, et al., [3], show that the proposed approach performs better than the original approach.
关键词：3D-Content-based Shape Retrieval; Bag-Of-Features; SIFT; Vector Quantization; Codebook