Camera calibration based on the common self-polar triangle of sphere images

Haifei Huang, Hui Zhang*, Yiu Ming CHEUNG

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

5 Citations (Scopus)


Sphere has been used for camera calibration in recent years. In this paper, a new linear calibration method is proposed by using the common self-polar triangle of sphere images. It is shown that any two of sphere images have a common self-polar triangle. Accordingly, a simple method for locating the vertices of such triangles is presented. An algorithm for recovering the vanishing line of the support plane using these vertices is developed. This allows to find out the imaged circular points, which are used to calibrate the camera. The proposed method starts from an existing theory in projective geometry and recovers five intrinsic parameters without calculating the projected circle center, which is more intuitive and simpler than the previous linear ones. Experiments with simulated data, as well as real images, show that our technique is robust and accurate.

Original languageEnglish
Title of host publicationComputer Vision - ACCV 2014 - 12th Asian Conference on Computer Vision, Revised Selected Papers
EditorsMing-Hsuan Yang, Hideo Saito, Daniel Cremers, Ian Reid
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9783319168074
Publication statusPublished - 2015
Event12th Asian Conference on Computer Vision, ACCV 2014 - Singapore, Singapore
Duration: 1 Nov 20145 Nov 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th Asian Conference on Computer Vision, ACCV 2014

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)


Dive into the research topics of 'Camera calibration based on the common self-polar triangle of sphere images'. Together they form a unique fingerprint.

Cite this