Exploring the bag-of-words method for 3D shape retrieval

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 (PG) vs. global-to-global (GG) retrieval, and articulated vs. non-articulated; 2) The spatial information, which is represented as concentric spheres, is integrated into the framework to improve the discriminative capability; 3) the analysis of the experimental results on Purdue Engineering Benchmark (PEB) [4] reveals that some properties of the BW approach make it perform better on the PG task than the GG task. 4) The BW approach is evaluated on non-articulated database PEB [4] and articulated database McGill Shape Benchmark (MSB) [17] and compared to other methods. ©2009 IEEE.