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Investigating the Bag-of-Words Method for 3D Shape Retrieval

Published

Author(s)

Afzal A. Godil, Xiaolan Li

Abstract

This paper investigates the capabilities of the Bag-of-Words (BW) method in the 3D shape retrieval field. The contributions of this paper are: 1) the 3D shape retrieval task is categorized from different points of view: specific vs. generic, partial-to-global retrieval (PGR) vs. global-to- global retrieval (GGR), and articulated vs. non-articulated; 2) The spatial information, which represented as concentric spheres, is integrated into the framework to improve the discriminative ability; 3) the analysis of the experimental results on Purdue Engineering Benchmark (PEB) reveals that some properties of the BW approach make it perform better on the PGR task than the GGR task. 4) The BW approach is evaluated on non-articulated database PEB and articulated database McGill Shape Benchmark (MSB) and compared to other methods.
Citation
EURASIP Journal on Advances in Signal Processing
Volume
2010

Keywords

Bag-of-words, spin images, 3D shape retrieval, local features, partial matching, non-rigid matching

Citation

Godil, A. and Li, X. (2010), Investigating the Bag-of-Words Method for 3D Shape Retrieval, EURASIP Journal on Advances in Signal Processing, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=905907 (Accessed April 15, 2024)
Created June 30, 2010, Updated February 19, 2017