Out of Sight, Out of Sync: Understanding Conflict in Distributed Teams
Organization Science
Influencing group participation with a shared display
CSCW '04 Proceedings of the 2004 ACM conference on Computer supported cooperative work
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
ICMI '08 Proceedings of the 10th international conference on Multimodal interfaces
Meeting mediator: enhancing group collaborationusing sociometric feedback
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Human-Computer Interaction
Supporting Engagement and Floor Control in Hybrid Meetings
Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions
Automatic nonverbal analysis of social interaction in small groups: A review
Image and Vision Computing
Characterizing conversational group dynamics using nonverbal behaviour
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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This paper addresses two problems: Firstly, the problem of classifying remote and collocated small-group working meetings, and secondly, the problem of identifying the remote participant, using in both cases nonverbal behavioral cues. Such classifiers can be used to improve the design of remote collaboration technologies to make remote interactions as effective as possible to collocated interactions. We hypothesize that the difference in the dynamics between collocated and remote meetings is significant and measurable using speech activity based nonverbal cues. Our results on a publicly available dataset - the Augmented Multi-Party Interaction with Distance Access (AMIDA) corpus - show that such an approach is promising, although more controlled settings and more data are needed to explore the addressed problems further.