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Dynamic Bayesian Networks for Multimodal Interaction
Published on Feb 25, 200710504 Views
Dynamic Bayesian networks (DBNs) offer a natural upgrade path beyond classical hidden Markov models and become especially relevant when temporal data contains higher order structure, multiple modaliti
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Chapter list
Dynamic Bayesian Networks for Multimodal Interaction00:00
Outline02:00
Introduction04:17
Bayesian Networks06:54
Bayes Nets to Junction Trees11:01
Junction Tree Algorithm12:35
Junction Tree Algorithm14:57
Maximum Likelihood with EM15:58
Dynamic Bayes Nets19:52
Two-Person Interaction24:48
DBN: Hidden ARMA Model26:31
DBN: Hidden ARMA Model28:41
Hidden ARMA Features:29:34
Conditional EM for hidden ARMA29:48
Conditional EM31:19
Conditional EM32:31
Hidden ARMA on Gesture33:51
DBN: Input-Output HMM34:11
DBN: Input-Output HMM34:37
Input-Output HMM Data35:04
Video Representation35:46
Video Representation36:06
Input-Output HMM36:18
Input-Output HMM with CEM36:36
Input-Output HMM with CEM37:05
Input-Output HMM Results37:35
Intractable Dynamic Bayes Nets38:12
Intractable DBNs: Generalized EM38:43
Intractable DBNs Variational EM39:51
Dynamical System Trees40:44
Dynamical System Trees41:11
DSTs and Generalized EM41:55
DSTs for American Football42:07
DSTs for American Football42:18
DSTs for Gene Networks43:19
Robotic Surgery, Haptics & Video43:44
Robotic Surgery, Haptics & Video44:17
Robotic Surgery, Haptics & Video44:26
Robotic Surgical Drills Results45:03
Conclusion46:26