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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Guilbert, N., & Heyden, A. (2005). Contraction mapping calibration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3804 LNCS, pp. 678–683). https://doi.org/10.1007/11595755_85
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