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

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 correspondin...

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Bibliographic Details
Published in:Heliyon Vol. 10; no. 16; p. e35929
Main Authors: Rodriguez-Quiñonez, Julio C., Sanchez-Castro, Jonathan J., Real-Moreno, Oscar, Galaviz, Guillermo, Flores-Fuentes, Wendy, Sergiyenko, Oleg, Castro-Toscano, Moises J., Hernandez-Balbuena, Daniel
Format: Journal Article
Language:English
Published: England Elsevier Ltd 30.08.2024
Elsevier
Subjects:
algorithms
computer vision
Driver pose classification
Head pose estimation
industry
Landmark detection
Object detection
Stereo vision
Driver pose classification
Stereo vision
Head pose estimation
Landmark detection
Object detection
ISSN:2405-8440, 2405-8440
Online Access:Get full text
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Summary: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. •Concurrent Head pose estimation and object detection.•Continuous Head pose computation.•Driver alarm for dangerous situations.•Driver pose classification for attention assessment.•A real time ADAS system for detecting dangerous on low speed zones (school, neighborhoods, crosswalks, among others).
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ISSN:2405-8440
2405-8440
DOI:10.1016/j.heliyon.2024.e35929