REAL TIME PEDESTRIAN ALERT SYSTEM FOR VEHICLES

Year 2020, Volume: 21 Issue: 3, 446 - 453, 30.09.2020

Şahin Işık Göksu Vatansever Yıldıran Anagun Mehmet Çelikhan Kemal Özkan

https://doi.org/10.18038/estubtda.629701

Abstract

In this study, we have developed a pre-collision alert
system for vehicles in terms of detection pedestrians in road. The system is
consisting from deep learning models and transfer learning methodologies. For
this purpose, pre-trained convolutional models was considered to detect
pedestrian and road.  Finally, the
segmented road mask and pedestrian mask was utilized to reveal the intersection
of these two masks. The system generates an alert if the number of pixels is
higher than predefined threshold value. By considering the visual results, the
proposed system gives valuable detection results to avoid collision.

Keywords

Deep Learning Models, Pedestrian Alert System, Road Detection

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