Symmetry detection from realworld images competition 2013: Summary and results

Jingchen Liu, George Slota, Gang Zheng, Zhaohui Wu, Minwoo Park, Seungkyu Lee, Ingmar Rauschert, Yanxi Liu

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

58 Scopus citations

Abstract

Symmetry is a pervasive phenomenon presenting itself in all forms and scales in natural and manmade environments. Its detection plays an essential role at all levels of human as well as machine perception. The recent resurging interest in computational symmetry for computer vision and computer graphics applications has motivated us to conduct a US NSF funded symmetry detection algorithm competition as a workshop affiliated with the Computer Vision and Pattern Recognition (CVPR) Conference, 2013. This competition sets a more complete benchmark for computer vision symmetry detection algorithms. In this report we explain the evaluation metric and the automatic execution of the evaluation workflow. We also present and analyze the algorithms submitted, and show their results on three test sets of real world images depicting reflection, rotation and translation symmetries respectively. This competition establishes a performance baseline for future work on symmetry detection.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013
Pages200-205
Number of pages6
DOIs
StatePublished - Oct 8 2013
Event2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013 - Portland, OR, United States
Duration: Jun 23 2013Jun 28 2013

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Other

Other2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013
CountryUnited States
CityPortland, OR
Period6/23/136/28/13

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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