Abstract
Reliability and accuracy are key in state of the art Driving Assistance Systems and Autonomous Driving applications. These applications make use of sensor fusion for trustable obstacle detection and classification in any meteorological and illumination condition. Laser scanner and camera are widely used as sensors to fuse because of its complementary capabilities. This paper presents some novel techniques for automatic and unattended data alignment between sensors, and Artificial Intelligence techniques are used to use laser point clouds not only for obstacle detection but also for classification.. Information fusion with classification information from both laser scanner and camera improves overall system reliability.
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This Work Was Supported by the Spanish Government through the CICYT Project (TRA2013-48314-C3-1-R).
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Ponz, A., Rodríguez-Garavito, C.H., García, F., Lenz, P., Stiller, C., Armingol, J.M. (2015). Laser Scanner and Camera Fusion for Automatic Obstacle Classification in ADAS Application. In: Helfert, M., Krempels, KH., Klein, C., Donellan, B., Guiskhin, O. (eds) Smart Cities, Green Technologies, and Intelligent Transport Systems. SMARTGREENS VEHITS 2015 2015. Communications in Computer and Information Science, vol 579. Springer, Cham. https://doi.org/10.1007/978-3-319-27753-0_13
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DOI: https://doi.org/10.1007/978-3-319-27753-0_13
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