Abstract
The paper develops three extended Kalman filters (EKF) for 2D-3D pose estimation. The measurement models are based on three constraints which are constructed by geometric algebra. The dynamic measurements for these EKF are either points or lines. The real monocular vision experiments show that the results of EKFs perform more stable than that of LMS method.
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References
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Zhang, Y., Rosenhahn, B., Sommer, G. (2000). Extended Kalman Filter Design for Motion Estimation by Point and Line Observations. In: Sommer, G., Zeevi, Y.Y. (eds) Algebraic Frames for the Perception-Action Cycle. AFPAC 2000. Lecture Notes in Computer Science, vol 1888. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10722492_27
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DOI: https://doi.org/10.1007/10722492_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41013-3
Online ISBN: 978-3-540-45260-7
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