Abstract
This contribution presents an approach for the continuous self-calibration of an active stereo rig with verging cameras. The proposed self-calibration recovers extrinsic parameters up to scale as well as the focal lengths of both cameras. Three different categories of constraint equations are evaluated and formulated as a Gauss-Helmert model for self-calibration: bundle adjustment with reduced parameter vector, the epipolar constraint, and the trilinear constraints. The optimization of the constraints is implemented as a robust Iterated Extended Kalman Filter that allows initial stereo calibration as well as continuous tracking of the camera parameters. The performance of the algorithm is demonstrated on synthetic and real imagery.
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© 2006 Springer-Verlag Berlin Heidelberg
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Dang, T., Hoffmann, C. (2006). Tracking Camera Parameters of an Active Stereo Rig. In: Franke, K., Müller, KR., Nickolay, B., Schäfer, R. (eds) Pattern Recognition. DAGM 2006. Lecture Notes in Computer Science, vol 4174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861898_63
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DOI: https://doi.org/10.1007/11861898_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44412-1
Online ISBN: 978-3-540-44414-5
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