A Bayesian Fusion Approach and Its Application to Integrating Audio and Visual Signals in HCI
Pan, Hao
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Permalink
https://hdl.handle.net/2142/80738
Description
Title
A Bayesian Fusion Approach and Its Application to Integrating Audio and Visual Signals in HCI
Author(s)
Pan, Hao
Issue Date
2001
Doctoral Committee Chair(s)
Liang, Zhi-Pei
Department of Study
Electrical Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
Finally, kernel canonical correlation analysis (CCA) is developed to model nonlinear or high-order correlations between signals from two sources. Kernel CCA uses kernel principal component analysis (PCA), which elegantly combines a nonlinear transformation and linear PCA into a one-step calculation, so as to avoid the computational burden of high/infinite-dimensional nonlinear transformations.
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