Curved glide-reflection symmetry detection

Seungkyu Lee, Yanxi Liu

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

15 Scopus citations

Abstract

We generalize reflection symmetry detection to a curved glide-reflection symmetry detection problem. We propose a unifying, local feature-based approach for curved glidereflection symmetry detection from real, unsegmented images, where the classic reflection symmetry becomes one of four special cases. Our method detects and groups statistically dominant local reflection axes in a 3D parameter space. A curved glide-reflection symmetry axis is estimated by a set of contiguous local straight reflection axes. Experimental results of the proposed algorithm on 40 real world images demonstrate promising performance.

Original languageEnglish (US)
Title of host publication2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
PublisherIEEE Computer Society
Pages1046-1053
Number of pages8
ISBN (Print)9781424439935
DOIs
StatePublished - Jan 1 2009
Event2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Miami, FL, United States
Duration: Jun 20 2009Jun 25 2009

Publication series

Name2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
Volume2009 IEEE Computer Society Conference on Computer Vision and ...

Other

Other2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
CountryUnited States
CityMiami, FL
Period6/20/096/25/09

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

Cite this

Lee, S., & Liu, Y. (2009). Curved glide-reflection symmetry detection. In 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009 (pp. 1046-1053). [5206814] (2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009; Vol. 2009 IEEE Computer Society Conference on Computer Vision and ...). IEEE Computer Society. https://doi.org/10.1109/CVPRW.2009.5206814