Globally optimal hand-eye calibration

This paper introduces simultaneous globally optimal hand-eye self-calibration in both its rotational and translational components. The main contributions are new feasibility tests to integrate the hand-eye calibration problem into a branch-and-bound parameter space search. The presented method constitutes the first guaranteed globally optimal estimator for simultaneous optimization of both components with respect to a cost function based on reprojection errors. The system is evaluated in both synthetic and real world scenarios. The employed benchmark dataset is published online1 to create a common point of reference for evaluation of hand-eye self-calibration algorithms.

• Type: Journal
• Year: 2012
• Where: CVPR
• Authors: Thomas Ruland, Tomás Pajdla, Lars Krüger
• Keywords: Computer Vision, Cvpr 2012, Self Calibration, Simultaneous Optimization, World Scenarios