Detection of Traffic Violations of Road Users Based on Convolutional Neural Networks

Abstract

In this paper, we explore the implementation of vehicle and pedestrian detection based on neural networks in a real-world application. We suggest changes to the previously published method with respect to capabilities of low-powered devices, such as Nvidia Jetson platform. Our experimental evaluation shows that detectors are capable of running 10.7 FPS on Jetson TX2 and can be used in real-world applications.