Using Audio and Video Features to Classify the Most Dominant Person in a Group MeetingReport as inadecuate




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Presented at: "" Publication date: 2007

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.

Note: IDIAP-RR 07-29 Reference LIDIAP-CONF-2007-016





Author: Hung, Hayley; Jayagopi, Dinesh Babu; Yeo, Chuohao; Friedland, Gerald; Ba, Silèye O.; Odobez, Jean-Marc; Ramchandran, Kannan; Mirg

Source: https://infoscience.epfl.ch/record/146055?ln=en







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