An algorithm to calibrate field cameras for stereo clouds

Jiuxiang Hu, Anshuman Razdan, Joseph A. Zehnder

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

Abstract

This paper presents a robust extrinsic parameter estimation algorithm to calibrate field cameras which were used to observe the formation of clouds on a mountainous region. Generally, camera calibration needs accurate landmark survey and image feature identification. However, our observation area, is a large scale scene in a physically inaccessible area, therefore the landmark surveys are not precise. Since clouds are distant to cameras, cloud features in the images are also difficult to accurately identify for stereo correspondences. The noise in landmark, survey and cloud feature correspondence makes it challenging to obtain, desired cloud observation, accuracy by using traditional least, squares based camera, calibration approaches. Our camera calibration approach is based on a generalized total least square (GTLS) algorithm instead of a normal least square method. Experiments show that the GTLS-based camera calibration is more accurate and robust than LS-based methods for our application.

Original languageEnglish (US)
Title of host publication2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
PagesII1048-II1051
Edition1
DOIs
StatePublished - Dec 1 2008
Event2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings - Boston, MA, United States
Duration: Jul 6 2008Jul 11 2008

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Number1
Volume2

Other

Other2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
Country/TerritoryUnited States
CityBoston, MA
Period7/6/087/11/08

Keywords

  • Camera calibration
  • Geometric error
  • Intrinsic and extrinsic parameters
  • Total least squares

ASJC Scopus subject areas

  • Computer Science Applications
  • General Earth and Planetary Sciences

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