Multiple random walkers and their application to image cosegmentation

Chulwoo Lee, Won Dong Jang, Jae Young Sim, Chang-Su Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

58 Citations (Scopus)

Abstract

A graph-based system to simulate the movements and interactions of multiple random walkers (MRW) is proposed in this work. In the MRW system, multiple agents traverse a single graph simultaneously. To achieve desired interactions among those agents, a restart rule can be designed, which determines the restart distribution of each agent according to the probability distributions of all agents. In particular, we develop the repulsive rule for data clustering. We illustrate that the MRW clustering can segment real images reliably. Furthermore, we propose a novel image cosegmentation algorithm based on the MRW clustering. Specifically, the proposed algorithm consists of two steps: inter-image concurrence computation and intra-image MRW clustering. Experimental results demonstrate that the proposed algorithm provides promising cosegmentation performance.

Original languageEnglish
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherIEEE Computer Society
Pages3837-3845
Number of pages9
Volume07-12-June-2015
ISBN (Print)9781467369640
DOIs
Publication statusPublished - 2015 Oct 14
EventIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015 - Boston, United States
Duration: 2015 Jun 72015 Jun 12

Other

OtherIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
CountryUnited States
CityBoston
Period15/6/715/6/12

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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  • Cite this

    Lee, C., Jang, W. D., Sim, J. Y., & Kim, C-S. (2015). Multiple random walkers and their application to image cosegmentation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Vol. 07-12-June-2015, pp. 3837-3845). [7299008] IEEE Computer Society. https://doi.org/10.1109/CVPR.2015.7299008