Abstract
Localizing a vehicle with a vision based system often requires to match and track landmarks whose position is known. This paper tries to define a new method to track some features in modeling them as local planar patches with a monocular camera. First a learning sequence is recorded to compute the planar features and their orientation around landmarks tracked on several views. Then in the localization part, camera pose is predicted and features are transformed to fit with the scene as seen by the camera. Landmarks can then easily be matched and position is computed more accurately. With this method many features can be tracked on longer sequences than with standard methods, even if the camera is moving away from the learning trajectory. This improves the localization.
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Charmette, B., Royer, E., Chausse, F. (2009). Matching Planar Features for Robot Localization. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5875. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10331-5_19
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DOI: https://doi.org/10.1007/978-3-642-10331-5_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10330-8
Online ISBN: 978-3-642-10331-5
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