A clustering successive POCS algorithm for fast point matching

Wei Lian, Yan Liang, Quan Pan, Yong Mei Chen, Hong Cai Zhang

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

1 Scopus citations

Abstract

This paper proposes a clustering successive projections onto convex sets (CSPOCS) algorithm for enforcing two way constraints originated from point matching. Via point clustering, the problem of projection onto convex set (POCS) where the convex set is described by point correspondence's constraints is converted to the POCS problem where the convex set is described by cluster correspondence's constraints. Then the successive POCS (SPOCS) technique is employed to solve the POCS problem. The resulting algorithm can be viewed as a generalization of SPOCS by combining with clustering. Its precision and computational load are decided by the average radius of clusters. Experimental results demonstrate the effectiveness of the algorithm.

Original languageEnglish
Title of host publicationProceedings of the 2006 International Conference on Machine Learning and Cybernetics
Pages3903-3908
Number of pages6
DOIs
StatePublished - 2006
Event2006 International Conference on Machine Learning and Cybernetics - Dalian, China
Duration: 13 Aug 200616 Aug 2006

Publication series

NameProceedings of the 2006 International Conference on Machine Learning and Cybernetics
Volume2006

Conference

Conference2006 International Conference on Machine Learning and Cybernetics
Country/TerritoryChina
CityDalian
Period13/08/0616/08/06

Keywords

  • Clustering
  • POCS
  • Point matching

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