Volume 27 Issue 9 - Publication Date: 1 September 2008
Data Selection for Hand-eye Calibration: A Vector Quantization Approach
Jochen Schmidt Lauflabor Locomotion Laboratory, University of Jena, Dornburger Strasse 23, 07743 Jena, Germany Heinrich Niemann Lehrstuhl für Mustererkennung Universität Erlangen-Nürnberg 91058 Erlangen, Germany
This paper presents new vector quantization based methods for selecting well-suited data for hand-eye calibration from a given sequence of hand and eye movements. Data selection can improve the accuracy of classic hand-eye calibration, and make it possible in the first place in situations where the standard approach of manually selecting positions is inconvenient or even impossible, especially when using continuously recorded data. A variety of methods is proposed, which differ from each other in the dimensionality of the vector quantization compared to the degrees of freedom of the rotation representation, and how the rotation angle is incorporated. The performance of the proposed vector quantization based data selection methods is evaluated using data obtained from a manually moved optical tracking system (hand) and an endoscopic camera (eye).
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