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Proceedings Paper

Camera calibration with lens distortion using weakly localized image features
Author(s): Moumen T. Ahmed; Elsayed E. Hemayed; Aly A. Farag
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Paper Abstract

Camera calibration is a crucial problem for many industrial applications that incorporate visual sensing. In this paper, we present an approach to computing the intrinsic and extrinsic camera parameters taking into account radial lens distortion. The approach consists of directly searching for the camera parameters that best project 3D points of a calibration pattern onto intensity edges in a 2D image of this pattern without explicitly extracting the edges. Our approach can be considered an extension of Robert's method to obtain a more accurate camera model that adjusts for lens distortion. This approach tolerates less accuracy in the image features and avoids heavy dependence on individual, strongly-localized features since feature localization is instead included as part of the error measure used in the optimization process. After describing the details of our approach, the paper shows some experiments to evaluate the approach performance in terms of accuracy, sensitivity to initial conditions and reliability.

Paper Details

Date Published: 22 March 1999
PDF: 9 pages
Proc. SPIE 3650, Sensors, Cameras, and Applications for Digital Photography, (22 March 1999); doi: 10.1117/12.342856
Show Author Affiliations
Moumen T. Ahmed, Univ. of Louisville (United States)
Elsayed E. Hemayed, Univ. of Louisville (United States)
Aly A. Farag, Univ. of Louisville (United States)


Published in SPIE Proceedings Vol. 3650:
Sensors, Cameras, and Applications for Digital Photography
Nitin Sampat; Thomas Yeh, Editor(s)

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