Exploring the Bag-of-Words method for 3D shape retrieval

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) 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 and articulated database McGill Shape Benchmark (MSB) and compared to other methods.