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Generation of regions of interest with high potential to contain pedestrians using non-dense 3D reconstruction from monocular vision

Abstract:

Traffic accidents are a global public health problem, due to the high number of human victims and the elevated economic and social costs that generate. In this context, pedestrians are among the most important and vulnerable elements of the road scene that need to be protected. It is thus that, in this work an innovative proposal is presented where the monocular visual information is used to simulate the stereo vision, and from this: i) generate regions of interest (ROIs) with high possibility of containing a pedestrian, and ii) estimate the trajectory of the vehicle. Experiments have been developed into a dataset of images taken in several streets of Santiago (Regi n Metropolitana), Chile. This database was obtained using an experimental vehicle under real driving conditions during the day. The ROI detection rate is 86,6 % for distances less than 20 meters, 82,9 % for distances less than 30 meters and 76,2 % for distances less than 40 meters.