A novel 3D model retrieval approach based on model-partitioning and fuzzy relevance feedback

Kuan Sheng Zou, Chun Ho Wu, Wai Hung Ip, Ching Yuen Chan, Kai Leung Yung, Zeng Qiang Chen

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

Abstract

3D models play an important role in many applications, so there is an urgent need for an effective content based 3D model retrieval system. A variety of 3D model retrieval methods have been proposed in recent years. Shape distributions show superiority over other methods due to ease of computation and invariance to Euclidean motion, but there is poor retrieval performance for the loss in information. This paper introduces two model-partitioning methods to improve shape distributions, in which the two enhanced descriptors are combined with a fuzzy feedback method. Experimental results show that the proposed methods can achieve better retrieval performance.
Original languageEnglish
Title of host publicationSmart Materials and Intelligent Systems
PublisherTrans Tech Publications Ltd
Pages186-190
Number of pages5
ISBN (Print)9780878492237
DOIs
Publication statusPublished - 1 Jul 2011

Publication series

NameAdvanced Materials Research
Volume143-144
ISSN (Print)1022-6680

Keywords

  • 3D model retrieval
  • Fuzzy relevance feedback
  • Model-partitioning
  • Shape distribution

ASJC Scopus subject areas

  • Engineering(all)

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