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EISeg: Effective interactive segmentation

  • Utah State University
  • School of Computer Science and Technology (School of Software), Harbin Institute of Technology Weihai

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

Abstract

Interactive image segmentation is a popular and challenging task. User interactions, e.g., setting seeds or specifying bounding box, play a critical role in determining the performance of all interactive segmentation approaches. However, most methods focus on improving segmentation performance by integrating higher level information; and to the best of our knowledge, no work has been done to improve the effectiveness of user interactions yet. In this paper, we propose the effective interactive segmentation (EISeg) method based on Neutro-Connectedness, which provides user with objective visual clues for guiding interactions. The experiments demonstrate that the proposed EISeg method guides interaction effectively, and achieves better results with much less user interaction (averagely 2.3 foreground and 1.8 background seeds/image) than state-of-the-art approaches.

Original languageEnglish
Title of host publication2016 23rd International Conference on Pattern Recognition, ICPR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1982-1987
Number of pages6
ISBN (Electronic)9781509048472
DOIs
StatePublished - 1 Jan 2016
Externally publishedYes
Event23rd International Conference on Pattern Recognition, ICPR 2016 - Cancun, Mexico
Duration: 4 Dec 20168 Dec 2016

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume0
ISSN (Print)1051-4651

Conference

Conference23rd International Conference on Pattern Recognition, ICPR 2016
Country/TerritoryMexico
CityCancun
Period4/12/168/12/16

Keywords

  • Effectiveness of interaction
  • Interactive segmentation
  • Neutro-Connectedness

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