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A dynamic clustering algorithm based on artificial immune system for analyzing 3D models

  • Xianghua Li
  • , Chao Gao
  • , Tianyang Lv
  • , Li Tao
  • Southwest University
  • Harbin Engineering University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the field of content-based 3D model retrieval, classifying and organizing 3D model database is an important fundamental research, which is critical for improving the retrieval performance. Clustering is one of the most effective methods to classify 3D models. However, there has been little work on it. This paper proposes a dynamic clustering algorithm based on artificial immune system for classifying 3D models, which not only can classify existing models, but can deal with new incremental models. Experimental results show that our algorithm can obtain better classification of 3D models.

Original languageEnglish
Title of host publicationProceedings - 2012 8th International Conference on Natural Computation, ICNC 2012
Pages854-858
Number of pages5
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 8th International Conference on Natural Computation, ICNC 2012 - Chongqing, China
Duration: 29 May 201231 May 2012

Publication series

NameProceedings - International Conference on Natural Computation
ISSN (Print)2157-9555

Conference

Conference2012 8th International Conference on Natural Computation, ICNC 2012
Country/TerritoryChina
CityChongqing
Period29/05/1231/05/12

Keywords

  • 3D model retrieval
  • artifiial immune system
  • clustering
  • immune response

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