Abstract
This paper presents an efficient technique for real time estimation of on-board stereo vision system pose. The whole process is performed in the Euclidean space and consists of two stages. Initially, a compact representation of the original 3D data points is computed. Then, a RANSAC based least squares approach is used for fitting a plane to the 3D road points. Fast RANSAC fitting is obtained by selecting points according to a probability distribution function that takes into account the density of points at a given depth. Finally, stereo camera position and orientation—pose—is computed relative to the road plane. The proposed technique is intended to be used on driver assistance systems for applications such as obstacle or pedestrian detection. A real time performance is reached. Experimental results on several environments and comparisons with a previous work are presented.
This work has been partially supported by the Spanish Ministry of Education and Science under project TRA2004-06702/AUT. The first author was supported by The Ramón y Cajal Program. The third author was supported by Spanish Ministry of Education and Science grant BES-2005-8864.
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Sappa, A.D., Dornaika, F., Gerónimo, D., López, A. (2007). Efficient On-Board Stereo Vision Pose Estimation. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2007. EUROCAST 2007. Lecture Notes in Computer Science, vol 4739. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75867-9_148
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DOI: https://doi.org/10.1007/978-3-540-75867-9_148
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