An ontology and SWRL based 3D model retrieval system

Authors:
Xinying Wang;Tianyang Lv;Shengsheng Wang;Zhengxuan Wang
Affiliations:
College of Computer Science and Technology, Jilin University, Changchun, China and Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Cha ...;College of Comp. Sci. and Techn., Jilin Univ., Changchun, China and Key Lab. for Symbolic Computation and Knowledge Eng. of Ministry of Education, Jilin Univ., Changchun, China and College of Comp ...;College of Computer Science and Technology, Jilin University, Changchun, China and Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Cha ...;College of Computer Science and Technology, Jilin University, Changchun, China and Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Cha ...
Venue:
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
Year:
2008

Citing 4
Cited 0

X-means: Extending K-means with Efficient Estimation of the Number of Clusters

ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
The Princeton Shape Benchmark (Figures 1 and 2)

SMI '04 Proceedings of the Shape Modeling International 2004
Jena: implementing the semantic web recommendations

Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Three-dimensional shape searching: state-of-the-art review and future trends

Computer-Aided Design

Quantified Score

Hi-index	0.00

Visualization

Abstract

3D model retrieval is an important part of multimedia retrieval. However, the performance of traditional retrieval method of text-based and content-based is not satisfying because the keyword and the shape feature do not include the semantic information of the 3D models. The paper explores an ontology and SWRL-based 3D model retrieval system Onto3D. It can infer 3D models' semantic property by rule engine and retrieve the target models by ontology. The experiments on Princeton Shape Benchmark show that Onto3D achieves good performance not only in text retrieval but also in shape retrieval.