Probabilistic correspondence matching using random walk with restart

Research output: Contribution to conferencePaper

8 Citations (Scopus)

Abstract

This paper presents a probabilistic method for correspondence matching with a framework of the random walk with restart (RWR). The matching cost is reformulated as a corresponding probability, which enables the RWR to be utilized for matching the correspondences. There are mainly two advantages in our method. First, the proposed method guarantees the non-trivial steady-state solution of a given initial matching probability due to the restarting term in the RWR. It means the number of iteration, a crucial parameter which influences the performance of algorithm, is not needed in contrast to the conventional methods. This gives the consistent results regardless of the evolution time. Second, only an adjacent neighborhood is considered when the matching probabilities are inferred, which lowers the computational complexity while not sacrificing performance. Experimental results show that the performance of the proposed method is competitive to that of state-of-the-art methods both qualitatively and quantitatively.

Original languageEnglish
DOIs
Publication statusPublished - 2012
Event2012 23rd British Machine Vision Conference, BMVC 2012 - Guildford, Surrey, United Kingdom
Duration: 2012 Sep 32012 Sep 7

Other

Other2012 23rd British Machine Vision Conference, BMVC 2012
CountryUnited Kingdom
CityGuildford, Surrey
Period12/9/312/9/7

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Probabilistic correspondence matching using random walk with restart'. Together they form a unique fingerprint.

  • Cite this

    Oh, C., Ham, B., & Sohn, K. (2012). Probabilistic correspondence matching using random walk with restart. Paper presented at 2012 23rd British Machine Vision Conference, BMVC 2012, Guildford, Surrey, United Kingdom. https://doi.org/10.5244/C.26.37