Title
Hybrid shape descriptor and meta similarity generation for non-rigid and partial 3D model retrieval.
Abstract
Non-rigid and partial 3D model retrieval are two significant and challenging research directions in the field of 3D model retrieval. Little work has been done in proposing a hybrid shape descriptor that works for both retrieval scenarios, let alone the integration of the component features of the hybrid shape descriptor in an automatic way. In this paper, we propose a hybrid shape descriptor that integrates both geodesic distance-based global features and curvature-based local features. We also develop an automatic algorithm to generate meta similarity resulting from different component features of the hybrid shape descriptor based on Particle Swarm Optimization. Experimental results demonstrate the effectiveness and advantages of our framework, as well as the significant improvements in retrieval performances. The framework is general and can be applied to similar approaches that integrate more features for the development of a single algorithm for both non-rigid and partial 3D model retrieval.
Year
DOI
Venue
2014
10.1007/s11042-013-1464-2
Multimedia Tools and Applications
Keywords
Field
DocType
3D model retrieval, Non-rigid models, Partial similarity retrieval, Hybrid shape descriptor, Meta similarity
Particle swarm optimization,Computer vision,Pattern recognition,Computer science,Artificial intelligence,Geodesic
Journal
Volume
Issue
ISSN
72
2
1573-7721
Citations 
PageRank 
References 
20
0.56
65
Authors
3
Name
Order
Citations
PageRank
Bo Li125715.09
Afzal Godil261930.70
Henry Johan335529.36