en-de
en-es
en-fr
en-sl
en
en-zh
0.25
0.5
0.75
1.25
1.5
1.75
2
Dynamic Bayesian Networks for Multimodal Interaction
Published on Feb 25, 200710506 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
Related categories
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