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Stereo geometry from 3D ego-motion streams.

F Dornaika1, C R Chung

  • 1Dept. of Autom. & Comput.-Aided Eng., Chinese Univ. of Hong Kong, Shatin, China.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|February 2, 2008
PubMed
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This study introduces a new method for stereo rig geometry determination using motion correspondence, eliminating the need for stereo correspondence or reference objects. This advances online calibration for stereo cameras and robotic vision systems.

Area of Science:

  • Computer Vision
  • Robotics
  • 3D Geometry

Background:

  • Existing online stereo calibration methods rely heavily on stereo correspondence.
  • Determining stereo rig geometry under general rigid motion is challenging.
  • Reference objects are often required for accurate calibration.

Purpose of the Study:

  • To develop a novel framework for stereo rig geometry determination without stereo correspondence.
  • To enable online calibration for stereo cameras using motion correspondence.
  • To broaden the applicability of structure-from-motion strategies to stereo rigs.

Main Methods:

  • A mathematical framework utilizing motion correspondence for stereo geometry recovery.
  • Linear and nonlinear methods for solving camera rotation and translation.

Related Experiment Videos

  • Stability and accuracy analysis considering noise in image, camera, and ego-motion data.
  • Main Results:

    • Successful recovery of stereo rig geometry (rotation and translation) using motion correspondence.
    • Demonstrated robustness of the methods against various noise sources.
    • Experimental validation with real image data.

    Conclusions:

    • The proposed method significantly simplifies stereo rig calibration by avoiding stereo correspondence.
    • This framework enhances online calibration capabilities for stereo rigs.
    • Applicable to estimating 3D geometry for various mounted devices in vision and robotics.