Abstract
We present a direct method to calculate a 6DoF pose change of a monocular camera for mobile navigation. The calculated pose is estimated up to a constant unknown scale parameter that is kept constant over the entire reconstruction process. This method allows a direct calculation of the metric position and rotation without any necessity to fuse the information in a probabilistic approach over longer frame sequence as it is the case in most currently used VSLAM approaches. The algorithm provides two novel aspects to the field of monocular navigation. It allows a direct pose estimation without any a-priori knowledge about the world directly from any two images and it provides a quality measure for the estimated motion parameters that allows to fuse the resulting information in Kalman Filters.
We present the mathematical formulation of the approach together with experimental validation on real scene images.
Keywords
- Singular Value Decomposition
- Motion Parameter
- Rotation Matrix
- Camera Image
- Epipolar Line
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2008 Springer-Verlag Berlin Heidelberg
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Burschka, D., Mair, E. (2008). Direct Pose Estimation with a Monocular Camera. In: Sommer, G., Klette, R. (eds) Robot Vision. RobVis 2008. Lecture Notes in Computer Science, vol 4931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78157-8_34
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DOI: https://doi.org/10.1007/978-3-540-78157-8_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78156-1
Online ISBN: 978-3-540-78157-8
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