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Abstract: We describe a head-tracking system that harnesses Bayesian modality fusion, a technique for integrating the analyses of multiple visual tracking algorithms within a probabilistic framework. At the heart of the approach is a Bayesian network model that includes random variables that serve as context-sensitive indicators of reliability of the different tracking algorithms. Parameters of the Bayesian model are learned from data in an offline training phase using ground-truth data from a Polhemus... (Update)
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BibTeX entry: (Update)
@misc{ of-bayesian,
author = "Probabilistic Integration Of",
title = "Bayesian Modality Fusion:",
url = "citeseer.ist.psu.edu/668533.html" }
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