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Parallel feature based calibration method for a trinocular vision sensor
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DOI：10.1364/OE.393012.png)
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Abstract
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In this paper, a new method to calibrate a trinocular vision sensor is presented. A planar target with several parallel lines is utilized. The trifocal tensor of three image planes can be calculated out according to line correspondences. Compatible essential matrix between each two cameras can be obtained. Then, rotation matrix and translation matrix can be deduced base on singular value decomposition of their corresponding essential matrix. In our proposed calibration method, image rectification is carried out to remove perspective distortion. As the feature utilized is straight line, precise point to point correspondence is not necessary. Experimental results show that our proposed calibration method can obtain precise results. Moreover, the trifocal tensor can also give a strict constraint for feature matching as descripted in our previous work. Root mean square error of measured distances is 0.029 mm with regards to the view field of about 250x250 mm. As parallel feature exists widely in natural scene, our calibration method also provides a new approach for self-calibration of a trinocular vision sensor. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Keywords:
MULTI-CAMERA
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3.3
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6.1W
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14.3W
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Improved separated-parameter calibration method for binocular vision measurements with a large field of view.png)
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