Direct Vehicle Collision Detection from Motion in Driving Video

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2017-06
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English
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Abstract

The objective of this work is the instantaneous computation of Time-to-Collision (TTC) for potential collision only from motion information captured with a vehicle borne camera. The contribution is the detection of dangerous events and degree directly from motion divergence in the driving video, which is also a clue used by human drivers, without applying vehicle recognition and depth measuring in prior. Both horizontal and vertical motion divergence are analyzed simultaneously in several collision sensitive zones. Stable motion traces of linear feature components are obtained through filtering in the motion profiles. As a result, this avoids object recognition, and sophisticated depth sensing. The fine velocity computation yields reasonable TTC accuracy so that the video camera can achieve collision avoidance alone from size changes of visual patterns.

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Kilicarslan, M., & Zheng, J. Y. (2017). Direct vehicle collision detection from motion in driving video. In 2017 IEEE Intelligent Vehicles Symposium (IV) (pp. 1558–1564). https://doi.org/10.1109/IVS.2017.7995931
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2017 IEEE Intelligent Vehicles Symposium
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