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A framework for online simultaneous localization, mapping and self-calibration is presented which can detect and handle significant change in the calibration parameters. Estimates are computed in constant-time by factoring the problem and focusing on segments of the trajectory that are most informative for the purposes of calibration. A novel technique is presented to detect the probability that a...
This paper describes an extensible framework for real-time self-calibration of cameras in the simultaneous mapping and localization (SLAM) setting. The system is demonstrated to calibrate both pinhole and fish-eye camera models from unknown initial parameters while seamlessly solving the maximum likelihood online SLAM problem in real-time. Self-calibration is performed by tracking image features,...
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