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Intrinsic and extrinsic active self-calibration of multi-camera systems

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Abstract

We present a method for active self-calibration of multi-camera systems consisting of pan-tilt zoom cameras. The main focus of this work is on extrinsic self-calibration using active camera control. Our novel probabilistic approach avoids multi-image point correspondences as far as possible. This allows an implicit treatment of ambiguities. The relative poses are optimized by actively rotating and zooming each camera pair in a way that significantly simplifies the problem of extracting correct point correspondences. In a final step we calibrate the entire system using a minimal number of relative poses. The selection of relative poses is based on their uncertainty. We exploit active camera control to estimate consistent translation scales for triplets of cameras. This allows us to estimate missing relative poses in the camera triplets. In addition to this active extrinsic self-calibration we present an extended method for the rotational intrinsic self-calibration of a camera that exploits the rotation knowledge provided by the camera’s pan-tilt unit to robustly estimate the intrinsic camera parameters for different zoom steps as well as the rotation between pan-tilt unit and camera. Quantitative experiments on real data demonstrate the robustness and high accuracy of our approach. We achieve a median reprojection error of \(0.95\) pixel.

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Acknowledgments

Marcel Brückner would like to thank the Carl Zeiss Foundation (Carl-Zeiss-Stiftung) for supporting his research.

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  1. Friedrich Schiller University of Jena, Jena, Germany

    Marcel Brückner, Ferid Bajramovic & Joachim Denzler

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  1. Marcel Brückner
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  2. Ferid Bajramovic
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  3. Joachim Denzler
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Correspondence to Marcel Brückner.

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Brückner, M., Bajramovic, F. & Denzler, J. Intrinsic and extrinsic active self-calibration of multi-camera systems. Machine Vision and Applications 25, 389–403 (2014). https://doi.org/10.1007/s00138-013-0541-x

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