Abstract
This paper describes a novel method for estimating extrinsic camera parameters using both feature points on an image sequence and sparse position data acquired by GPS. Our method is based on a structure-from-motion technique but is enhanced by using GPS data so as to minimize accumulative estimation errors. Moreover, the position data are also used to remove mis-tracked features. The proposed method allows us to estimate extrinsic parameters without accumulative errors even from an extremely long image sequence. The validity of the method is demonstrated through experiments of estimating extrinsic parameters for both synthetic and real outdoor scenes.
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© 2006 Springer-Verlag Berlin Heidelberg
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Yokochi, Y., Ikeda, S., Sato, T., Yokoya, N. (2006). Extrinsic Camera Parameter Estimation Based-on Feature Tracking and GPS Data. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612032_38
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DOI: https://doi.org/10.1007/11612032_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31219-2
Online ISBN: 978-3-540-32433-1
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