Abstract:
Technological advancement and the density of cars endanger the safety of pedestrians and drivers, which is an increasingly real concern that stimulates all areas in findi...Show MoreMetadata
Abstract:
Technological advancement and the density of cars endanger the safety of pedestrians and drivers, which is an increasingly real concern that stimulates all areas in finding solutions. Whether or not the driver wears a seat belt, whether the vehicle is moving at speed or not, these indicators in the event of an impact are just as valuable and influence the safety of the driver and other road users. Movement analysis and processing, manual search, sensor detection, and recording of movements will expose the problem of high costs and labor as well as long development time. This paper addresses the analysis and classification by detecting the movement and presence of driver's belts by contextual analysis and detection in the area of incidence of the angle support pole in which the seat belt is located. Detecting the edges in a gradient model and performing the probabilities of broadly extracting the presence of the belt. This module makes a part of a platform dedicated to safe driving, based on communication vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-everything (V2X) and visible light communications (VLC), augmented reality, pedestrian detection, obstacles, vehicles and emotional states, factors that influence the driving style.
Date of Conference: 08-10 October 2020
Date Added to IEEE Xplore: 23 November 2020
ISBN Information:
Print on Demand(PoD) ISSN: 2372-1618