Driver distraction is a leading factor in car crashes. With a goal to reduce traffic accidents
and improve transportation safety, this study proposes a driver distraction detection system …

Facial expressions are a significant part of non-verbal communication. Recognizing facial
expressions of people with neurological disorders is essential because these people may …

Awareness of the road scene is an essential component for both autonomous vehicles and
Advances Driver Assistance Systems and is gaining importance both for the academia and …

Distracted driving is one of the main contributors to traffic accidents. This paper proposes a
deep learning approach to detecting multiple distracted driving behaviors. In order to obtain …

Vehicle driver distraction is one of the major reasons for road accidents. Involvement with a
co-passenger, use of in-vehicle devices or phone leads to a situation where the driver head …

We address the issues of 3-D head pose estimation and face modeling from a depth image.
Given a depth image, random forests are effective for estimating the location and orientation …

Electroencephalography (EEG) signals have been proven to be effective in evaluating
human's cognitive state under specific tasks. Conventional classification models utilized for …

Head pose estimation has been a key task in computer vision since a broad range of
applications often requires accurate information about the orientation of the head. Achieving …

Head pose estimation is an important problem as it facilitates tasks such as gaze estimation
and attention modeling. In the automotive context, head pose provides crucial information …

The ability to detect, localize and classify objects that are anomalies is a challenging task in
the computer vision community. In this paper, we tackle these tasks developing a framework …