@article{(Open Science Index):https://publications.waset.org/pdf/450, title = {Robust Camera Calibration using Discrete Optimization}, author = {Stephan Rupp and Matthias Elter and Michael Breitung and Walter Zink and Christian Küblbeck}, country = {}, institution = {}, abstract = {Camera calibration is an indispensable step for augmented reality or image guided applications where quantitative information should be derived from the images. Usually, a camera calibration is obtained by taking images of a special calibration object and extracting the image coordinates of projected calibration marks enabling the calculation of the projection from the 3d world coordinates to the 2d image coordinates. Thus such a procedure exhibits typical steps, including feature point localization in the acquired images, camera model fitting, correction of distortion introduced by the optics and finally an optimization of the model-s parameters. In this paper we propose to extend this list by further step concerning the identification of the optimal subset of images yielding the smallest overall calibration error. For this, we present a Monte Carlo based algorithm along with a deterministic extension that automatically determines the images yielding an optimal calibration. Finally, we present results proving that the calibration can be significantly improved by automated image selection.}, journal = {International Journal of Computer and Information Engineering}, volume = {2}, number = {7}, year = {2008}, pages = {2435 - 2439}, ee = {https://publications.waset.org/pdf/450}, url = {https://publications.waset.org/vol/19}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 19, 2008}, }