Abstract
A camera calibration method based on a nonlinear modeling function of an artificial neural network (ANN) is proposed in this paper. With the application of the nonlinear mapping feature of an ANN, the proposed method successfully finds the relationship between image coordinates without explicitly calculating all the camera parameters, including position, orientation, focal length, and lens distortion. Experiments on the estimation of 2-D coordinates of image world given 3-D space coordinates are performed. In comparison with Tsai’s two stage method, the proposed method reduced modeling errors by 11.45% on average.
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© 2006 Springer-Verlag Berlin Heidelberg
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Woo, DM., Park, DC. (2006). Implicit Camera Calibration Using an Artificial Neural Network. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893257_72
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DOI: https://doi.org/10.1007/11893257_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46481-5
Online ISBN: 978-3-540-46482-2
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