Abstract
This paper is focused on the use of 2D vision for motion estimation of an underwater Remotely Operated Vehicle. A monocular vision system allows the extraction of characteristic lines in the current image of the observed scene. The 3D camera motion estimation involves a matching between these 2D visual features and those obtained in the previous image. The camera has been calibrated and its intrinsic parameters are known.
We describe the image processing we have implemented to extract the geometrical features from the current image, and the method used to track these features in a sequence of images. Experimental results obtained with real subsea images are presented.
We present the algorithm which has been implemented to estimate the 3D camera displacement. We show that the rotation matrix and the translation vector can be solved for separately. Simulations have been carried out with synthetic images in order to investigate how the accuracy of this algorithm would be affected by the image noise, and by the feature characteristics.
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© 1998 Springer-Verlag London Limited
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Wasielewski, S., Aldon, M.J., Strauss, O. (1998). Monocular Vision Applied to Accurate ROV Localization. In: Zelinsky, A. (eds) Field and Service Robotics. Springer, London. https://doi.org/10.1007/978-1-4471-1273-0_48
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DOI: https://doi.org/10.1007/978-1-4471-1273-0_48
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