Communication using manual (hand) gestures is considered a defining property of social
robots, and their physical embodiment and presence, therefore, we see a need for a …

This paper summarizes the 2021 ChaLearn Looking at People Challenge on Understanding
Social Behavior in Dyadic and Small Group Interactions (DYAD), which featured two tracks …

Non-verbal social human behavior forecasting has increasingly attracted the interest of the
research community in recent years. Its direct applications to human-robot interaction and …

Most manual communicative gestures that humans produce cannot be looked up in a
dictionary, as these manual gestures inherit their meaning in large part from the …

In all architectures tested, a first embedding layer transformed the input coordinates and
offsets from all landmarks into an intermediate representation vector of size 512 by means of …

This paper presents a human–robot interaction system (HRIS) that utilizes human
perception and action recognition to enable the robot to understand human intentions and …

Social robots facilitate improved human–robot interactions through nonverbal behaviors
such as handshakes or hugs. However, the traditional methods, which rely on precoded …

In this paper, we propose a virtual agent application. We develop a virtual agent that reacts
to gestures and a virtual environment in which it can interact with the user. We capture …

Deep learning has shown tremendous potential for transforming healthcare by enabling
more accurate diagnoses, improved treatment planning and better patient outcome …

In recent years," computational empathy" has emerged as a new challenging research field.
Computational empathy investigates how artificial agents can manifest empathic behaviours …