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» PAC-Learning of Markov Models with Hidden State
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NAACL
2003
13 years 8 months ago
Implicit Trajectory Modeling through Gaussian Transition Models for Speech Recognition
It is well known that frame independence assumption is a fundamental limitation of current HMM based speech recognition systems. By treating each speech frame independently, HMMs ...
Hua Yu, Tanja Schultz
CVIU
2008
126views more  CVIU 2008»
13 years 6 months ago
Optimising dynamic graphical models for video content analysis
A key problem in video content analysis using dynamic graphical models is to learn a suitable model structure given some observed visual data. We propose a Completed Likelihood AI...
Tao Xiang, Shaogang Gong
UAI
2004
13 years 8 months ago
Dynamical Systems Trees
We propose dynamical systems trees (DSTs) as a flexible model for describing multiple processes that interact via a hierarchy of aggregating processes. DSTs extend nonlinear dynam...
Andrew Howard, Tony Jebara
MMS
2006
13 years 6 months ago
View-invariant motion trajectory-based activity classification and recognition
Motion trajectories provide rich spatio-temporal information about an object's activity. The trajectory information can be obtained using a tracking algorithm on data streams ...
Faisal I. Bashir, Ashfaq A. Khokhar, Dan Schonfeld
ICPR
2008
IEEE
14 years 1 months ago
Optimal feature weighting for the continuous HMM
We propose new Continuous Hidden Markov Model (CHMM) structure that integrates feature weighting component. We assume that each feature vector could include different subsets of f...
Oualid Missaoui, Hichem Frigui