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Catadioptric camera calibration using geometric invariants.

Xianghua Ying1, Zhanyi Hu

  • 1National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, PR China. xhying@nlpr.ia.ac.cn

IEEE Transactions on Pattern Analysis and Machine Intelligence
|January 12, 2005
PubMed
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This study introduces a new method for calibrating central catadioptric cameras using geometric invariants from lines and spheres. The sphere-based approach offers superior robustness and accuracy for camera calibration.

Area of Science:

  • Computer Vision
  • Geometric Optics
  • Robotics

Background:

  • Central catadioptric cameras offer wide field-of-view imaging with a single viewpoint.
  • Accurate camera calibration is crucial for applications relying on 3D reconstruction and scene understanding.

Purpose of the Study:

  • To propose a novel geometric invariant-based method for calibrating central catadioptric cameras.
  • To compare the performance of line-based versus sphere-based calibration techniques.

Main Methods:

  • Utilizing geometric invariants derived from the projection of lines and spheres onto the catadioptric image plane.
  • Deriving intrinsic camera parameter constraint equations from these invariants.
  • Developing two variants of the calibration method: one using line projections and another using sphere projections.

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Main Results:

  • Projections of lines yield three invariants, while sphere projections yield two.
  • Calibration can be achieved using projections of two lines or three spheres.
  • The sphere-based method demonstrates higher robustness and accuracy compared to the line-based method.

Conclusions:

  • A novel and effective method for central catadioptric camera calibration has been presented.
  • The sphere projection-based calibration method is recommended for its superior performance.
  • The method's efficacy is validated through simulations and real-world experimental results.