Using audio and video features to classify the most dominant person in a group meeting

Authors:
Hayley Hung;Dinesh Jayagopi;Chuohao Yeo;Gerald Friedland;Sileye Ba;Jean-Marc Odobez;Kannan Ramchandran;Nikki Mirghafori;Daniel Gatica-Perez
Affiliations:
IDIAP Research Institute, Martigny, Switzerland;IDIAP, Martigny, Switzerland & Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland;University of California, Berkeley;International Computer Science Institute (ICSI), Berkeley;IDIAP Research Institute, Martigny, Switzerland;IDIAP, Martigny, Switzerland & Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland;University of California, Berkeley;International Computer Science Institute (ICSI), Berkeley;IDIAP, Martigny, Switzerland & Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
Venue:
Proceedings of the 15th international conference on Multimedia
Year:
2007

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Abstract

The automated extraction of semantically meaningful information from multi-modal data is becoming increasingly necessary due to the escalation of captured data for archival. A novel area of multi-modal data labelling, which has received relatively little attention, is the automatic estimation of the most dominant person in a group meeting. In this paper, we provide a framework for detecting dominance in group meetings using different audio and video cues. We show that by using a simple model for dominance estimation we can obtain promising results.