Abstract
In this paper a new calibration scheme for recovering Euclidian camera parameters from their affine of projective primitives is presented. It is based on a contraction mapping implying that the obtained solution is unique, i.e. no local minimas threaten to yield a non-optimal solution. The approach unifies Euclidian calibration from affine and projective configurations and fewer cameras (m ≥ 2) need to be available than in traditional schemes. The algorithm is validated on synthetic and real data.
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© 2005 Springer-Verlag Berlin Heidelberg
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Guilbert, N., Heyden, A. (2005). Contraction Mapping Calibration. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_85
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DOI: https://doi.org/10.1007/11595755_85
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30750-1
Online ISBN: 978-3-540-32284-9
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