Abstract
In the present work, a novel approach to the monocular visual odometry problem is detailed. More powerful and robust techniques such as convex optimisation with the L ∞ norm and the H ∞ Filter are adopted. Using monocular systems makes the motion estimation challenging due to the absolute scale ambiguity caused by projective effects. For this, we propose robust tools to estimate both the trajectory of a moving object and the unknown absolute scale ratio between consecutive image pairs. The proposed solution uses as input only images provided by a single camera mounted on the roof of a ground vehicle. Experimental evaluations showed that convex optimisation with the L ∞ norm and the robust H ∞ Filter clearly outperforms classical methods based on least squares and Levenberg-Marquardt algorithms.
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Boulekchour, M., Aouf, N. (2013). L ∞ Norm Based Solution for Visual Odometry. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40246-3_23
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DOI: https://doi.org/10.1007/978-3-642-40246-3_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40245-6
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