@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 K├╝blbeck},
	  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},