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3D Similarity Search Using a Weighted Structural Histogram Representation

  • Tong Lu
  • Rongjun Gao
  • Tuantuan Wang
  • Yubin Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6297)

Abstract

A fast and robust 3D retrieval method is proposed based on a novel weighted structural histogram representation. Our method has the following steps: 1) adaptively segment any 3D shape into a group of meaningful parts to generate local distribution matrixes, 2) integrate all the local distribution matrixes into a global distribution matrix, simultaneously considering their weight factors, and 3) retrieve 3D shapes by calculating the distance between their global distribution matrixes. Experimental results show that our method is effective and efficient for 3D shape retrieval and robust to translation, scaling or rotation transformations.

Keywords

3D comparison local distribution global distribution weighted structural distribution 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Tong Lu
    • 1
    • 2
  • Rongjun Gao
    • 1
  • Tuantuan Wang
    • 1
  • Yubin Yang
    • 1
  1. 1.State Key Lab. for Novel Software TechnologyNanjing UniversityNanjingChina
  2. 2.Jiangyin Institute of Information Technology of Nanjing UniversityChina

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