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Title:Structure Inference for Bayesian Multisensory Perception and Tracking
Authors: Timothy Hospedales ; Joel Cartwright ; Sethu Vijayakumar
Date:Jan 2007
Publication Title:International Joint Conference on Artificial Intelligence (IJCAI 2007)
Publication Type:Conference Paper Publication Status:Published
Page Nos:2122-2128
We investigate a solution to the problem of multi-sensor perception and tracking by formulating it in the framework of Bayesian model selection. Humans robustly associate multi-sensory data as appropriate, but previous theoretical work has focused largely on purely integrative cases, leaving segregation unaccounted for and unexploited by machine perception systems. We illustrate a unifying, Bayesian solution to multi-sensor perception and tracking which accounts for both integration and segregation by explicit probabilistic reasoning about data association in a temporal context. Unsupervised learning of such a model with EM is illustrated for a real world audio-visual application.
2006 by The University of Edinburgh. All Rights Reserved
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Bibtex format
author = { Timothy Hospedales and Joel Cartwright and Sethu Vijayakumar },
title = {Structure Inference for Bayesian Multisensory Perception and Tracking},
book title = {International Joint Conference on Artificial Intelligence (IJCAI 2007)},
year = 2007,
month = {Jan},
pages = {2122-2128},
doi = {},
url = {},

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