Estimation of radial distortion using local spectra of planar textures

A novel self-calibration method for estimation of radial lens distortion is proposed. It requires only a single image of a textured plane that may have arbitrary orientation with respect to the camera. A frequency-based approach is used to estimate the perspective and non-linear lens distortions tha...

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Bibliographic Details
Published in2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) pp. 472 - 477
Main Authors Spitschan, Benjamin, Ostermann, Jorn
Format Conference Proceeding
LanguageEnglish
Published MVA Organization 01.05.2017
Subjects
Calibration
Cameras
Estimation
Lenses
Nonlinear distortion
Optical distortion
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Summary:A novel self-calibration method for estimation of radial lens distortion is proposed. It requires only a single image of a textured plane that may have arbitrary orientation with respect to the camera. A frequency-based approach is used to estimate the perspective and non-linear lens distortions that planar textures are subject to when projected to a camera image plane. The texture is only required to be homogeneous and may exhibit a high amount of stochastic content. For this purpose, we derive the relationship between the local spatial frequencies of the texture and those of the image. In a joint optimization, both the rotation matrix and the radial distortion are subsequently estimated. Results show that with appropriate textures, a mean reprojection error of 9.76 · 10 -5 relative to the picture width is achieved. In addition, the method is robust to image corruption by noise.
DOI:10.23919/MVA.2017.7986903