A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2005; you can also visit the original URL.
The file type is application/pdf
.
A self-calibrating algorithm for speaker tracking based on audio-visual statistical models
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
doi:10.1109/icassp.2002.5745023
dblp:conf/icassp/BealJA02
fatcat:bj3tg5uu4ra6ncaejs5ri4r4v4