Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …

Motor vehicle crashes are great threats to our life, which may result in numerous fatalities, as
well as tremendous economic and societal costs. Driver inattention, either distraction or …

Head pose estimation (HPE) is an active and popular area of research. Over the years,
many approaches have constantly been developed, leading to a progressive improvement …

Driver attention modeling is a crucial technique in building human-centric intelligent driving
systems. Considering the human visual mechanism, this study leverages multi-level visual …

A smart vehicle should be able to monitor the actions and behaviors of the human driver to
provide critical warnings or intervene when necessary. Recent advancements in deep …

Driver behavior is an essential factor affecting traffic safety, and driver behavior monitoring
systems (DMSs) are widely exploited in intelligent transportation systems to reduce the risk …

We present TICaM, a Time-of-flight In-car Cabin Monitoring dataset for vehicle interior
monitoring using a single wide-angle depth camera. Our dataset addresses the deficiencies …

Accurate vision-based driver attention estimation is a challenging task due to the limitations
of the visual sensor, and it is a critical and fundamental function of building a human …

The interest in driver monitoring has grown recently, especially in the context of autonomous
vehicles. However, the training of deep neural networks for computer vision requires more …

Deep learning methods have proven useful for head pose estimation, but the effect of their
depth, type and input resolution based on infrared (IR) images still need to be explored. In …