PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Automatic Analysis of Multimodal Group Actions in Meetings
Iain McCowan, Daniel Gatica-Perez, Samy Bengio, Guillaume Lathoud, Mark Barnard and Dong Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence Volume 27, Number 3, pp. 305-317, 2005.

Abstract

This paper investigates the recognition of group actions in meetings. A statistical framework is proposed in which group actions result from the interactions of the individual participants. The group actions are modelled using different HMM-based approaches, where the observations are provided by a set of audio-visual features monitoring the actions of individuals. Experiments demonstrate the importance of taking interactions into account in modelling the group actions. It is also shown that the visual modality contains useful information, even for predominantly audio-based events, motivating a multimodal approach to meeting analysis.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Speech
Multimodal Integration
ID Code:1100
Deposited By:Samy Bengio
Deposited On:26 September 2005