Abstract
The main goal of an overtaking monitor system is the segmentation and tracking of the overtaking vehicle. This application can be addressed through an optic flow driven scheme. We can focus on the rear mirror visual field by placing a camera on the top of it. If we drive a car, the ego-motion optic flow pattern is more or less unidirectional, i.e. all the static objects and landmarks move backwards while the overtaking cars move forward towards our vehicle. This well structured motion scenario facilitates the segmentation of regular motion patterns that correspond to the overtaking vehicle. Our approach is based on two main processing stages: first, the computation of optical flow using a novel superpipelined and fully parallelized architecture capable to extract the motion information with a frame-rate up to 148 frames per second at VGA resolution (640x480 pixels). Second, a tracking stage based on motion pattern analysis provides an estimated position of the overtaking car. We analyze the system performance, resources and show some promising results using a bank of overtaking car sequences.
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Díaz, J., Ros, E., Mota, S., Agis, R. (2006). Real-Time Embedded System for Rear-View Mirror Overtaking Car Monitoring. In: Vassiliadis, S., Wong, S., Hämäläinen, T.D. (eds) Embedded Computer Systems: Architectures, Modeling, and Simulation. SAMOS 2006. Lecture Notes in Computer Science, vol 4017. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11796435_39
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DOI: https://doi.org/10.1007/11796435_39
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