Name
Abstract | ||
|---|---|---|
This paper investigates the capabilities of the Bag-of-Words (BWs) 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 versus generic, partial-toglobal retrieval (PGR) versus global-to-global retrieval (GGR), and articulated versus nonarticulated (2) the spatial information, 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 nonarticulated database PEB and articulated database McGill Shape Benchmark (MSB) and compared to other methods. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1155/2010/108130 | EURASIP J. Adv. Sig. Proc. |
Keywords | Field | DocType |
purdue engineering benchmark,pgr task,bag-of-words method,mcgill shape benchmark,bw approach,ggr task,shape retrieval task,global-to-global retrieval,shape retrieval field,articulated database,partial-toglobal retrieval,bag of words | Spatial analysis,Bag-of-words model,Computer vision,Computer science,Artificial intelligence,Discriminative model,Machine learning,Visual Word | Journal |
Volume | Issue | ISSN |
2010, | 1 | 1687-6180 |
Citations | PageRank | References |
6 | 0.40 | 23 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaolan Li | 1 | 91 | 7.14 |
| Afzal Godil | 2 | 619 | 30.70 |