Stereo Camera Head-Eye Calibration Based on Minimum Variance Approach Using Surface Normal Vectors

This paper presents a stereo camera-based head-eye calibration method that aims to find the globally optimal transformation between a robot's head and its eye. This method is highly intuitive and simple, so it can be used in a vision system for humanoid robots without any complex procedures. To...

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Veröffentlicht in:Sensors (Basel, Switzerland) Switzerland), 2018-10, Vol.18 (11), p.3706
Hauptverfasser: Lee, Joong-Jae, Jeong, Mun-Ho
Format: Artikel
Sprache:eng
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Zusammenfassung:This paper presents a stereo camera-based head-eye calibration method that aims to find the globally optimal transformation between a robot's head and its eye. This method is highly intuitive and simple, so it can be used in a vision system for humanoid robots without any complex procedures. To achieve this, we introduce an extended minimum variance approach for head-eye calibration using surface normal vectors instead of 3D point sets. The presented method considers both positional and orientational error variances between visual measurements and kinematic data in head-eye calibration. Experiments using both synthetic and real data show the accuracy and efficiency of the proposed method.
ISSN:1424-8220
1424-8220
DOI:10.3390/s18113706