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Hier finden Sie wissenschaftliche Publikationen aus den FraunhoferInstituten. Robust estimation of camera parameters using combinatorial optimization
 Gobbetti, E. ; International Association of Science and Technology for Development IASTED: Ninth IASTED International Conference Computer Graphics and Imaging. Proceedings. CDROM : Innsbruck, Austria, 13.02.200715.02.2007 Anaheim, CA: ACTA Press, 2007 ISBN: 9780889866454 ISBN: 9780889866447 S.18590 
 International Conference Computer Graphics and Imaging (CGIM) <9, 2007, Innsbruck> 

 Englisch 
 Konferenzbeitrag 
 Fraunhofer IIS () 
Abstract
The estimation of the parameters of the visual system is an indispensable step for augmented reality or image guided applications where quantitative information should be derived from the images. Usually, the estimation process is called camera calibration and it is performed by observing a special calibration object from different directions. From these observations the image coordinates of the projected calibration marks are extracted and the mapping from the 3D world coordinates to the 2D image coordinates is calculated. To attain a wellsuited mapping, the calibration images must suffice certain constraints in order to ensure that the underlying mathematical algorithms are wellposed. Thus, the choice of the input images influences the estimation process and consequence the quality of the derived information. In this paper we present a generic approach for camera calibration that is robust against illposed configurations. For this, we apply combinatorial optimization technique in order to determine the optimal subset of the pool of acquired images yielding the best calibration result with respect to the model fit error. Our approach is generic in the sense that it is independent of a certain calibration algorithm because it only makes use of a quality measure that acts as an objective function for the optimization.