Multimodal data collection for social interaction analysis in-the-wild

Conference Paper (2019)
Author(s)

Hayley Hung (TU Delft - Pattern Recognition and Bioinformatics)

Chirag Raman (TU Delft - Pattern Recognition and Bioinformatics)

E. Gedik (TU Delft - Pattern Recognition and Bioinformatics)

S. Tan (TU Delft - Pattern Recognition and Bioinformatics)

J.D. Vargas-Quiros (TU Delft - Pattern Recognition and Bioinformatics)

Research Group
Pattern Recognition and Bioinformatics
Copyright
© 2019 H.S. Hung, C.A. Raman, E. Gedik, S. Tan, J.D. Vargas Quiros
DOI related publication
https://doi.org/10.1145/3343031.3351320
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 H.S. Hung, C.A. Raman, E. Gedik, S. Tan, J.D. Vargas Quiros
Research Group
Pattern Recognition and Bioinformatics
Pages (from-to)
2714-2715
ISBN (electronic)
9781450368896
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

The benefits of exploiting multi-modality in the analysis of human-human social behaviour has been demonstrated widely in the community. An important aspect of this problem is the collection of data-sets that provide a rich and realistic representation of how people actually socialize with each other in real life. These subtle coordination patterns are influenced by individual beliefs, goals, and, desires related to what an individual stands to lose or gain in the activities they perform in their every day life. These conditions cannot be easily replicated in a lab setting and require a radical re-thinking of both how and what to collect. This tutorial provides a guide on how to create such multi-modal multi-sensor data sets when holistically considering the entire experimental design and data collection process.

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