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Scale-Space Clustering on the Sphere

  • Yoshihiko Mochizuki
  • Atsushi Imiya
  • Kazuhiko Kawamoto
  • Tomoya Sakai
  • Akihiko Torii
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8047)

Abstract

We present an algorithm for scale-space clustering of point cloud on the sphere using the methodology for the estimation of the density distribution of the points in the linear scale space. Our algorithm regards the union of observed point sets as an image defined by the delta functions located at the positions of the points on the sphere. A blurred version of this image has a deterministic structure which qualitatively represents the density distribution of the points in a point cloud on a manifold.

Keywords

Probability Density Function Point Cloud Leaf Node Heat Kernel Scale Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yoshihiko Mochizuki
    • 1
  • Atsushi Imiya
    • 2
  • Kazuhiko Kawamoto
    • 3
  • Tomoya Sakai
    • 4
  • Akihiko Torii
    • 5
  1. 1.Faculty of Science and EngineeringWaseda UniversityShinjuku-kuJapan
  2. 2.Institute of Management and Information TechnologiesChiba UniversityJapan
  3. 3.Academic Link CenterChiba UniversityInage-kuJapan
  4. 4.Department of Computer and Information SciencesNagasaki UniversityNagasakiJapan
  5. 5.Department of Control EngineeringTokyo Institute of TechnologyMeguro-kuJapan

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