A camera self-calibration method based on IOS-PSO

Jianping Xu, Fang Deng

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

4 Citations (Scopus)

Abstract

When reconstructing the 3D coordinates of an object in the real world, the necessary step is camera calibration. However, traditional methods cannot achieve online calibration , and active vision methods can not realize specific camera motion. In this paper, self-calibration based on Kruppa equations is adopted for camera calibration and IOS-PSO is presented for the optimization of the cost function. Although it is quick for PSO to converge to the globally optimal solution, heavily numerical oscillation occurs when there are high-dimensional independent variables. For more accurate results, the searching intervals are respectively divided into four small intervals and the searching results follow the defined rules. The experiment results show that the method achieves more accurate camera calibration results and high convergence rate.

Original languageEnglish
Title of host publicationProceedings - 2015 Chinese Automation Congress, CAC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages489-494
Number of pages6
ISBN (Electronic)9781467371896
DOIs
Publication statusPublished - 13 Jan 2016
EventChinese Automation Congress, CAC 2015 - Wuhan, China
Duration: 27 Nov 201529 Nov 2015

Publication series

NameProceedings - 2015 Chinese Automation Congress, CAC 2015

Conference

ConferenceChinese Automation Congress, CAC 2015
Country/TerritoryChina
CityWuhan
Period27/11/1529/11/15

Keywords

  • 3D coordinates
  • IOS-PSO
  • Kruppa equations
  • camera self-calibration

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