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Globally optimal camera-and-rotation-sensor calibration with a branch-and-bound algorithm

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Abstract

This paper introduces a globally optimal algorithm for obtaining the rotational displacement between the coordinate frames of a rotation sensor and a camera that are rigidly attached. Our method minimizes the geometrically meaningful error using a branch-and-bound algorithm to find the global solution. For this, we derive a bounding inequality and corresponding feasibility problem for a top-down efficient search over the rotation space to minimize the L1-, L2-, or L-norm error function. Experiments are performed with synthetic and real data sets to show the efficacy of the algorithm.

© 2017 Optical Society of America

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