Using Audio and Video Features to Classify the Most Dominant Person in a Group Meeting
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.
To appear in Association for Computing Machinery - Multimedia (ACM-MM), September 23--28, 2007, Augsburg, Bavaria, Germany.
Record created on 2010-02-11, modified on 2016-08-08