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Viewpoint information-theoretic measures for 3D shape similarity

  • Chinese Academy of Sciences

Research output: Chapter in Book/Conference proceedingConference proceedingpeer-review

1 Citation (Scopus)

Abstract

We present an information-theoretic framework to compute the shape similarity between 3D polygonal models. From an information channel between a sphere of viewpoints and the polygonal mesh of a model, an information sphere is obtained and used as a shape descriptor of the model. Given two models, the minimum distance between their information spheres, the distance between their information histograms, and the difference of their mutual information are introduced as methods to calculate the similarity matrix between 3D models. The performance of these techniques is tested using the Princeton Shape Benchmark database.

Original languageEnglish
Title of host publicationProceedings - VRCAI 2013
Subtitle of host publication12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry
PublisherAssociation for Computing Machinery
Pages183-189
Number of pages7
ISBN (Print)9781450325905
DOIs
Publication statusPublished - 2013
Event12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry, VRCAI 2013 - Hong Kong, Hong Kong
Duration: 17 Nov 201319 Nov 2013

Publication series

NameProceedings - VRCAI 2013: 12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry

Conference

Conference12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry, VRCAI 2013
Country/TerritoryHong Kong
CityHong Kong
Period17/11/1319/11/13

Keywords

  • information theory
  • mutual information
  • shape similarity

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