Calibration of radially symmetric distortion based on linearity in the calibrated image

Jun Fujiki, Hideitsu Hino, Shotaro Akaho, Noboru Murata

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

1 Citation (Scopus)

Abstract

For calibration of general radially symmetric distortion of omnidirectional cameras such as fish-eye lenses, calibration parameters are usually estimated so that curved lines, which are supposed to be straight in the real-world, are mapped to straight lines in the calibrated image, which is called plumbline principle. Under the principle, the camera with radially symmetric distortion can be calibrated by at least one distorted line in a image, theoretically, and the calibrated image is equivalent to the image taken by an ideal pin-hole camera. In this paper, the method to optimize the calibration parameters by maximizing the sum of the straightness, which is invariant under translation, rotation and magnification (scaling), of distorted lines on calibrated image is proposed. The performance of the proposed method is evaluated by artificial data and a real image.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
Pages288-295
Number of pages8
DOIs
Publication statusPublished - 2011 Dec 1
Event2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011 - Barcelona, Spain
Duration: 2011 Nov 62011 Nov 13

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Conference

Conference2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
CountrySpain
CityBarcelona
Period11/11/611/11/13

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ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Cite this

Fujiki, J., Hino, H., Akaho, S., & Murata, N. (2011). Calibration of radially symmetric distortion based on linearity in the calibrated image. In 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011 (pp. 288-295). [6130255] (Proceedings of the IEEE International Conference on Computer Vision). https://doi.org/10.1109/ICCVW.2011.6130255