From Real-time Attention Assessment to “With-me-ness” in Human-Robot Interaction

Measuring ``how much the human is in the interaction'' -- the level of engagement -- is instrumental in building effective interactive robots. Engagement, however, is a complex, multi-faceted cognitive mechanism that is only indirectly observable. This article formalizes with-me-ness as one of such indirect measures. With-me-ness, a concept borrowed from the field of Computer-Supported Collaborative Learning, measures in a well-defined way to what extent the human is with the robot over the course of an interactive task. As such, it is a meaningful precursor of engagement. We expose in this paper the full methodology, from real-time estimation of the human's focus of attention (relying on a novel, open-source, vision-based head pose estimator), to on-line computation of with-me-ness. We report as well on the experimental validation of this approach, using a naturalistic setup involving children during a complex robot-teaching task.

Published in:
Proceedings of the 2016 ACM/IEEE Human-Robot Interaction Conference, 157-164
Presented at:
11th ACM/IEEE Conference on Human-Robot Interaction, Christchurch, New Zealand, 2016
New York, Ieee

Note: The status of this file is: EPFL only

 Record created 2016-02-22, last modified 2018-01-28

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