Human gaze provides valuable information on human focus and intentions, making it a
crucial area of research. Recently, deep learning has revolutionized appearance-based …

Distracted or drowsy driving is unsafe driving behavior responsible for thousands of crashes
every year. Studying driver behavior has challenges associated with observing drivers in …

Driver's eye gaze holds a wealth of cognitive and intentional cues crucial for intelligent
vehicles. Despite its significance research on in-vehicle gaze estimation remains limited due …

Driving safety has been a concern since the first cars appeared on the streets. Driver
inattention has been singled out as a major cause of accidents early on. This is hardly …

Driver gaze plays a key role in different gaze-based applications, such as driver
attentiveness detection, visual distraction detection, gaze behavior understanding, and …

Human factors are a primary cause of vehicle accidents. Driver monitoring systems, utilizing
a range of sensors and techniques, offer an effective method to monitor and alert drivers to …

As a non-invasive method, vision-based driver monitoring aims to identify risky maneuvers
for intelligent vehicles and it has gained an increasing interest over recent years. However …

End-to-end autonomous driving has witnessed remarkable progress. However, the
extensive deployment of autonomous vehicles has yet to be realized, primarily due to 1) …

This article presents a synthetic distracted driving (SynDD1) dataset for machine learning
models to detect and analyze drivers' various distracted behavior and different gaze zones …

Eye gaze is an important natural behavior in social interaction as it delivers complex
exchanges between observer and observed, by building up the geometric constraints and …