Abstract
This study deals with the estimation of the road surface markings and their class using an onboard camera in an Advanced Driver Assistance System (ADAS). The proposed classification is performed in 3 successive steps corresponding to 3 levels of abstraction from the pixel to the object level through the connected-component one. At each level, a Markov Random Field models the a priori knowledge about object intrinsic features and object interactions, in particular spatial interactions. The proposed algorithm has been applied to simulated data simulated in various road configurations: dashed or continuous lane edges, road input, etc. These first results are very promising.
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Ammar, M., Le Hégarat-Mascle, S., Mounier, H. (2011). Road Surface Marking Classification Based on a Hierarchical Markov Model. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21596-4_35
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DOI: https://doi.org/10.1007/978-3-642-21596-4_35
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