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Related Experiment Videos

Error analysis of pure rotation-based self-calibration.

Lei Wang1, Sing Bing Kang, Heung-Yeung Shum

  • 1Department of Computer Science and Technology, Tsinghua University, Beijing 100084, PR China. wanglei99@mails.tsinghua.edu.cn

IEEE Transactions on Pattern Analysis and Machine Intelligence
|September 21, 2004
PubMed
Summary

Self-calibration for intrinsic camera parameters is reliable with pure rotation. This study analyzes errors from translation, finding translation-independent solutions under specific conditions for improved camera calibration.

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Area of Science:

  • Computer Vision
  • Robotics
  • Photogrammetry

Background:

  • Self-calibration is a standard method for determining intrinsic camera parameters.
  • Pure rotation is assumed for reliable self-calibration, but is difficult to achieve in practice.
  • Unwanted translation during camera motion introduces errors in intrinsic parameter recovery.

Purpose of the Study:

  • To analyze the impact of translation on intrinsic camera parameter accuracy during self-calibration.
  • To derive error expressions for recovered parameters under translational motion.
  • To identify conditions under which translation-independent solutions are feasible.

Main Methods:

  • Derived closed-form error expressions for intrinsic parameters from a single image pair with non-degenerate motion.

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  • Conducted repeated experiments to analyze multi-rotation scenarios lacking closed-form solutions.
  • Evaluated the influence of translational motion on camera self-calibration accuracy.

    • Main Results:

    • Quantified errors in intrinsic camera parameters caused by translational motion.
    • Demonstrated the existence of translation-independent solutions under specific practical conditions.
    • Provided insights into selecting optimal self-calibration strategies based on motion characteristics.

    Conclusions:

    • The presence of translation significantly affects the accuracy of self-calibrated intrinsic camera parameters.
    • Translation-independent solutions can be achieved, offering robustness in real-world applications.
    • The error analysis aids in choosing the most reliable self-calibration method for given scenarios.