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Toward an Attentive Robotic Architecture: Learning-Based Mutual Gaze Estimation in Human–Robot Interaction

Authors :
Maria Lombardi
Elisa Maiettini
Davide De Tommaso
Agnieszka Wykowska
Lorenzo Natale
Source :
Frontiers in Robotics and AI, Vol 9 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

Social robotics is an emerging field that is expected to grow rapidly in the near future. In fact, it is increasingly more frequent to have robots that operate in close proximity with humans or even collaborate with them in joint tasks. In this context, the investigation of how to endow a humanoid robot with social behavioral skills typical of human–human interactions is still an open problem. Among the countless social cues needed to establish a natural social attunement, this article reports our research toward the implementation of a mechanism for estimating the gaze direction, focusing in particular on mutual gaze as a fundamental social cue in face-to-face interactions. We propose a learning-based framework to automatically detect eye contact events in online interactions with human partners. The proposed solution achieved high performance both in silico and in experimental scenarios. Our work is expected to be the first step toward an attentive architecture able to endorse scenarios in which the robots are perceived as social partners.

Details

Language :
English
ISSN :
22969144
Volume :
9
Database :
Directory of Open Access Journals
Journal :
Frontiers in Robotics and AI
Publication Type :
Academic Journal
Accession number :
edsdoj.92193c3f9f6640628eba94edf29e60e6
Document Type :
article
Full Text :
https://doi.org/10.3389/frobt.2022.770165