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.
Original language | English |
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Publication status | Published - 2013 |
Event | ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2013 - Zurich, Switzerland Duration: 8 Sept 2013 → 12 Sept 2013 |
Workshop
Workshop | ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2013 |
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Abbreviated title | UbiComp 2013 |
Country/Territory | Switzerland |
City | Zurich |
Period | 8/09/13 → 12/09/13 |