@conference {13145,
	title = {Multimodal Tracking for Smart Videoconferencing and Video Surveillance},
	booktitle = {Computer Vision and Pattern Recognition, 2007. CVPR {\textquoteright}07. IEEE Conference on},
	year = {2007},
	month = {2007/06//},
	pages = {1 - 2},
	abstract = {Many applications require the ability to track the 3-D motion of the subjects. We build a particle filter based framework for multimodal tracking using multiple cameras and multiple microphone arrays. In order to calibrate the resulting system, we propose a method to determine the locations of all microphones using at least five loudspeakers and under assumption that for each loudspeaker there exists a microphone very close to it. We derive the maximum likelihood (ML) estimator, which reduces to the solution of the non-linear least squares problem. We verify the correctness and robustness of the multimodal tracker and of the self-calibration algorithm both with Monte-Carlo simulations and on real data from three experimental setups.},
	keywords = {(numerical, 3D, algorithm;smart, analysis;least, approximations;particle, arrays;nonlinear, cameras;multiple, Carlo, estimator;multimodal, filter;self-calibration, Filtering, least, likelihood, methods);teleconferencing;video, methods;image, microphone, MOTION, motion;Monte-Carlo, problem;particle, processing;video, signal, simulations;maximum, squares, surveillance;, surveillance;Monte, tracking;multiple, videoconferencing;video},
	doi = {10.1109/CVPR.2007.383525},
	author = {Zotkin,Dmitry N and Raykar,V.C. and Duraiswami, Ramani and Davis, Larry S.}
}
