Introducing authority and hubness into graph matching

  • Yu Ren Zhang
  • , Xu Yang
  • , Hong Qiao
  • , Li Jin Xu
  • , Wei You

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

Abstract

Spectral matching is an efficient approach for inexact graph matching. Many spectral matching methods boil down to power iteration which calculate the confidence vector iteratively. Inspired by the Web page ranking method Hypertext Induced Topic Search (HITS), we introduce hubness vector and authority vector to replace the traditional confidence vector, and an iterative algorithm is proposed to solve the subgraph matching problem. The incorporation of hubness and authority can help reduce the distraction caused by outliers, and provides better robustness against outliers. The performance of the proposed algorithm is evaluated on both synthetic graphs and real-world images.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Mechatronics and Automation, ICMA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages982-987
Number of pages6
ISBN (Electronic)9781479970964
DOIs
StatePublished - 2 Sep 2015
Externally publishedYes
Event12th IEEE International Conference on Mechatronics and Automation, ICMA 2015 - Beijing, China
Duration: 2 Aug 20155 Aug 2015

Publication series

Name2015 IEEE International Conference on Mechatronics and Automation, ICMA 2015

Conference

Conference12th IEEE International Conference on Mechatronics and Automation, ICMA 2015
Country/TerritoryChina
CityBeijing
Period2/08/155/08/15

Keywords

  • Graph Matching
  • HITS
  • Power Iteration

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