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Mixing implicit and explicit probes: Finding a ground truth for engagement in social human-robot interactions
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2014 (English)In: HRI '14 Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction, IEEE Computer Society, 2014, 140-141 p.Conference paper (Refereed)
Abstract [en]

In our work we explore the development of a computational model capable of automatically detecting engagement in social human-robot interactions from real-time sensory and contextual input. However, to train the model we need to establish ground truths of engagement from a large corpus of data collected from a study involving task and social-task engagement. Here, we intend to advance the current state-of-the-art by reducing the need for unreliable post-experiment questionnaires and costly time-consuming annotation with the novel introduction of implicit probes. A non-intrusive, pervasive and embedded method of collecting informative data at different stages of an interaction.

Place, publisher, year, edition, pages
IEEE Computer Society, 2014. 140-141 p.
, ACM/IEEE International Conference on Human-Robot Interaction, ISSN 2167-2148
Keyword [en]
Engagement, Ground truth, Human-robot interaction, Machine learning, Social tasks
National Category
Human Computer Interaction
URN: urn:nbn:se:kth:diva-145468DOI: 10.1145/2559636.2559815ScopusID: 2-s2.0-84897008442ISBN: 978-145032658-2OAI: diva2:718699
9th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2014; Bielefeld; Germany; 3 March 2014 through 6 March 2014

QC 20140522

Available from: 2014-05-22 Created: 2014-05-21 Last updated: 2014-05-22Bibliographically approved

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Peters, Christopher
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High Performance Computing and Visualization (HPCViz)
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ReferencesLink to record
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