Tracking focus of attention in meetings

The author presents an overview of his work on tracking focus of attention in meeting situations. He has developed a system capable of estimating participants´ focus of attention from multiple cues. In the system he employs an omni-directional camera to simultaneously track the faces of participants sitting around a meeting table and uses neural networks to estimate their head poses. In addition, he uses microphones to detect who is speaking. The system predicts participants´ focus of attention from acoustic and visual information separately, and then combines the output of the audio- and video-based focus of attention predictors. In addition he reports recent experimental results: In order to determine how well we can predict a subject´s focus of attention solely on the basis of his or her head orientation, he has conducted an experiment in which he recorded head and eye orientations of participants in a meeting using special tracking equipment. The results demonstrate that head orientation was a sufficient indicator of the subjects´ focus target in 89% of the time. Furthermore he discusses how the neural networks used to estimate head orientation can be adapted to work in new locations and under new illumination conditions.