Human-robot teams collaborating to achieve tasks under various conditions, especially in
unstructured, dynamic environments will require robots to adapt autonomously to a human …

Intention prediction has become a relevant field of research in Human-Machine and Human-
Robot Interaction. Indeed, any artificial system (co)-operating with and along humans …

In this paper, we present EV-Eye, a first-of-its-kind large scale multimodal eye tracking
dataset aimed at inspiring research on high-frequency eye/gaze tracking. EV-Eye utilizes an …

Intention recognition is the process of using behavioural cues, such as deliberative actions,
eye gaze, and gestures, to infer an agent's goals or future behaviour. In artificial intelligence …

Sensing and machine learning advances have enabled the unobtrusive measurement of
physiological responses and facial expressions so as to estimate one's cognitive …

Despite the importance of attention in user performance, current methods for attention
classification do not allow to discriminate between different attention types. We propose a …

Recent advances in eye tracking have given birth to a new genre of gaze-based context
sensing applications, ranging from cognitive load estimation to emotion recognition. To …

In this work, we present GazeGraph, a system that leverages human gazes as the sensing
modality for cognitive context sensing. GazeGraph is a generalized framework that is …

E-learning has emerged as an indispensable educational mode in the post-epidemic era.
However, this mode makes it difficult for students to stay engaged in learning without …

Video has become an essential medium for learning. However, there are challenges when
using traditional methods to measure how learners attend to lecture videos in video learning …