Abstract
Side-impact crashes have now become more important than head-on crashes, probably reflecting improvements in protecting occupants. Overtaking scenarios are one of the most dangerous situations in driving. This paper is concerned with a vision-based system on the rear-view mirror for safety in overtaking scenarios. A bio-inspired algorithm segments overtaking vehicles using motion information and rigid-body-motion criterion. The overtaking scene in the rear-view mirror is distorted due to perspective. Therefore we need to devise a way of reducing the distortion effect in order to enhance the segmentation capabilities of a vision system based on motion detection. We adopt a space variant mapping strategy. In this paper we describe a computing architecture that finely pipelines all the processing stages to achieve reliable high frame-rate processing.
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Mota, S., Ros, E., Díaz, J., Rodriguez, R., Carrillo, R. (2007). A Space Variant Mapping Architecture for Reliable Car Segmentation. In: Diniz, P.C., Marques, E., Bertels, K., Fernandes, M.M., Cardoso, J.M.P. (eds) Reconfigurable Computing: Architectures, Tools and Applications. ARC 2007. Lecture Notes in Computer Science, vol 4419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71431-6_31
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DOI: https://doi.org/10.1007/978-3-540-71431-6_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71430-9
Online ISBN: 978-3-540-71431-6
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