  This contribution gives an overview of face recogni-tion algorithms, their
implementation and practical uses. First, a training set of different persons'
faces has to be collected and used to train a face recognizer. The resulting
face model can be utilized to classify people in specific individuals or
unknowns. After tracking the recognized face and estimating the acoustic sound
source's position, both can be combined to give detailed information about
possible speakers and if they are talking or not. This leads to a precise
real-time description of the situation, which can be used for further
applications, e.g. for multi-channel speech enhancement by adaptive
beamformers.
