A self-calibrating algorithm for speaker tracking based on audio-visual statistical models

Matthew J. Beal, Nebojsa Jojic, Hagai Attias
2002 IEEE International Conference on Acoustics Speech and Signal Processing  
We present a self-calibrating algorithm for audio-visual tracking using two microphones and a camera. The algorithm uses a parametrized statistical model which combines simple models of video and audio. Using unobserved variables, the model describes the process that generates the observed data. Hence, it is able to capture and exploit the statistical structure of the audio and video data, as well as their mutual dependencies. The model parameters are estimated by the EM algorithm; object
more » ... tes are learned and automatic calibration is performed as part of this procedure. Tracking is done by Bayesian inference of the object location using the model. Successful performance is demonstrated on real multimedia clips.
doi:10.1109/icassp.2002.5745023 dblp:conf/icassp/BealJA02 fatcat:bj3tg5uu4ra6ncaejs5ri4r4v4