CQPOCS algorithm for fast feature point matching

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

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

A clustering and quadratic programming based projection onto convex sets (CQPOCS) algorithm for fast feature point matching is presented in this paper. Via feature point clustering, the problem of matching model point set and taget point set is converted in to the problem of matching corresponding clusters, thus reducing the computational cost. Then, quadratic programming based POCS algorithm is used to solve the cluster matching problem without incurring the successive POCS algorithm's accumulating deviation due to successive projections onto row convex sets and column convex sets. Simulation results show that our CQPOCS algorithm has satisfactory matching accuracy and computational safety.

Original languageEnglish
Pages (from-to)240-247
Number of pages8
JournalZidonghua Xuebao/Acta Automatica Sinica
Volume33
Issue number3
DOIs
StatePublished - Mar 2007

Keywords

  • Clustering
  • POCS
  • Point matching

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