Abstract
We present a method for actively calibrating a multi-camera system consisting of pan-tilt zoom cameras. After a coarse initial calibration, we determine the probability of each relative pose using a probability distribution based on the camera images. The relative poses are optimized by rotating and zooming each camera pair in a way that significantly simplifies the problem of extracting correct point correspondences. In a final step we use active camera control, the optimized relative poses, and their probabilities to calibrate the complete multi-camera system with a minimal number of relative poses. During this process we estimate the translation scales in a camera triangle using only two of the three relative poses and no point correspondences. Quantitative experiments on real data outline the robustness and accuracy of our approach.
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Brückner, M., Denzler, J. (2010). Active Self-calibration of Multi-camera Systems. In: Goesele, M., Roth, S., Kuijper, A., Schiele, B., Schindler, K. (eds) Pattern Recognition. DAGM 2010. Lecture Notes in Computer Science, vol 6376. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15986-2_4
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DOI: https://doi.org/10.1007/978-3-642-15986-2_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15985-5
Online ISBN: 978-3-642-15986-2
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