Global optimization of extended hand-eye calibration

Abstract

This paper introduces simultaneous global optimization of both camera orientation and vehicle wheel circumference without requiring any information about the translations in the system. The main contribution are new objective function bounds to integrate this problem into a branch-and-bound parameter space search. The presented method constitutes the first guaranteed globally optimal estimator for both components of the problem with respect to a cost function based on reprojection errors. The algorithm operates directly on image measurements and does not depend on any structure and motion preprocessing to estimate camera poses. The complete system is implemented and validated on both synthetic and real automotive datasets.