A Hybrid Computer Vision Framework for Real-Time Driver Fatigue and Distraction Detection Using Deep Learning
Year: 2026
Type: article
Abstract: Driver fatigue and distraction are critical behavioral states that require reliable, non-contact, and computationally efficient methods for real-time monitoring.This study presents a hybrid computer vision framework that combines interpretable geometric features with deep-learning-based object detection.The framework integrates Eye Aspect Ratio (EAR), Percentage of Eye Closure (PERCLOS), Mouth Aspect Ratio (MAR), head pose estimation, gaze direction analysis, and convolutional neural network (CNN)-based mobile phone detection within a unified multimodal architecture.A
Source: Engineered Science
DOI: 10.30919/es2633
Authors: Indira Uvaliyeva, Bauyrzhan Smakanov
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7224133264