Bridge motion to collision alarming using driving video
Mehmet Kılıçarslan, Jiang Yu Zheng · 2016
the objective of this work is to compute the Time-to-Collision (TTC) of surrounding vehicles of a vehicle using motion information in driving video. The key advantage in this work is the extraction of potential danger without vehicle detection and recognition in prior, but directly from the motion divergence in the video. We analyze the trace expansion both horizontally and vertically condensed in the collision sensitive zones in the driving video. Long term motion is stably obtained through filtering in the spatial-temporal video profiles at collision sensitive parts in the video. This overcomes the accuracy problem in object recognition and saved the computation cost tremendously in the real time 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.