Systematic evaluation of social behaviour modelling with a single accelerometer

Authors:
Hayley Hung;Gwenn Englebienne
Affiliations:
Technical University of Delft, Delft, Netherlands;University of Amsterdam, Amsterdam, Netherlands
Venue:
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Year:
2013

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Abstract

We describe our ongoing research on systematically analysing what types of socially related attributes and behaviours can be estimated automatically in highly social and crowded situations. This is a challenging task because obtaining the true labels for social behaviours or attributes in practice is non-trivial. Here, individuals hang a sensing device around their neck that records their acceleration during a social event. We then devise models to estimate their social behaviour or attributes based on these measurements and systematically evaluate the feasibility of such a set-up. Since we only use a single triaxial accelerometer per person, our results are surprisingly accurate and suggest that further socially relevant information could also be extracted. Our systematic evaluations provide a deeper understanding of how to better model socially relevant information in the future.