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What you see is what you get [self-calibrating camera lens distortion]

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2 Author(s)
Yan Meng ; Dept. of Electr. & Comput. Eng., Stevens Inst. of Technol., Hoboken, NJ, USA ; Hanqi Zhuang

A self-calibration method is presented for self-calibrating camera lens distortion by using only the image correspondences of two views. Two images of a single object are related by the epipolar geometry, which can be described by a 3 × 3 singular matrix called fundamental matrix. It captures all geometric information contained in two images. An optimization method is applied to minimize the epipolar distances of the two images by adjusting the camera lens radial distortion coefficient. The merit of the method is that it does not rely on any ground truth data. Simulation and experimental results are given to demonstrate the applicability of the method.

Published in:

IEEE Robotics & Automation Magazine  (Volume:11 ,  Issue: 4 )