A real-time vehicle safety system by concurrent object detection and head pose estimation via stereo vision.

Autor:	Rodriguez-Quiñonez JC; Universidad Autónoma de Baja California, Facultad de Ingeniería, Blvd. Benito Juárez S/N, 21280, Mexicali, Baja California, Mexico., Sanchez-Castro JJ; Universidad Autónoma de Baja California, Facultad de Ingeniería, Blvd. Benito Juárez S/N, 21280, Mexicali, Baja California, Mexico., Real-Moreno O; Universidad Autónoma de Baja California, Facultad de Ingeniería, Blvd. Benito Juárez S/N, 21280, Mexicali, Baja California, Mexico., Galaviz G; Universidad Autónoma de Baja California, Facultad de Ingeniería, Blvd. Benito Juárez S/N, 21280, Mexicali, Baja California, Mexico., Flores-Fuentes W; Universidad Autónoma de Baja California, Facultad de Ingeniería, Blvd. Benito Juárez S/N, 21280, Mexicali, Baja California, Mexico., Sergiyenko O; Instituto de Ingeniería, Universidad Autónoma de Baja California, Calle de la Normal S/N y Blvd. Benito Juárez, Col. Insurgentes Este, 21280, Mexicali, Baja California, Mexico., Castro-Toscano MJ; Universidad Autónoma de Baja California, Facultad de Ingeniería, Blvd. Benito Juárez S/N, 21280, Mexicali, Baja California, Mexico., Hernandez-Balbuena D; Universidad Autónoma de Baja California, Facultad de Ingeniería, Blvd. Benito Juárez S/N, 21280, Mexicali, Baja California, Mexico.
Jazyk:	angličtina
Zdroj:	Heliyon [Heliyon] 2024 Aug 07; Vol. 10 (16), pp. e35929. Date of Electronic Publication: 2024 Aug 07 (Print Publication: 2024).
DOI:	10.1016/j.heliyon.2024.e35929
Abstrakt:	A considerable number of vehicular accidents occur in low-millage zones like school streets, neighborhoods, and parking lots, among others. Therefore, the proposed work aims to provide a novel ADAS system to warn about dangerous scenarios by analyzing the driver's attention and the corresponding distances between the vehicle and the detected object on the road. This approach is made possible by concurrent Head Pose Estimation (HPE) and Object/Pedestrian Detection. Both approaches have shown independently their viable application in the automotive industry to decrease the number of vehicle collisions. The proposed system takes advantage of stereo vision characteristics for HPE by enabling the computation of the Euler Angles with a low average error for classifying the driver's attention on the road using neural networks. For Object Detection, stereo vision is used to detect the distance between the vehicle and the approaching object; this is made with a state-of-the-art algorithm known as YOLO-R and a fast template matching technique known as SoRA that provides lower processing times. The result is an ADAS system designed to ensure adequate braking time, considering the driver's attention on the road and the distances to objects. Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (© 2024 The Authors.)
Databáze:	MEDLINE
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