Stereo Camera Head-Eye Calibration Based on Minimum Variance Approach Using Surface Normal Vectors
Keyword(s):
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.
2009 ◽
Vol 19
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pp. s243-s249
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2010 ◽
Vol 33
(7)
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pp. 806-822
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2016 ◽
Vol 2016
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pp. 1-13
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2014 ◽
Vol 2
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2017 ◽