Abstract
Omnidirectional vision is highly beneficial for robot navigation. We present a novel perspective pose estimation for omnidirectional vision involving a parabolic central catadioptric sensor using line-plane correspondences. We incorporate an appropriate and approved stochastic method to deal with uncertainties in the data.
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Gebken, C., Tolvanen, A., Sommer, G. (2006). Pose Estimation from Uncertain Omnidirectional Image Data Using Line-Plane Correspondences. In: Franke, K., Müller, KR., Nickolay, B., Schäfer, R. (eds) Pattern Recognition. DAGM 2006. Lecture Notes in Computer Science, vol 4174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861898_59
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DOI: https://doi.org/10.1007/11861898_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44412-1
Online ISBN: 978-3-540-44414-5
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