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» Fuzzy Observable Markov Models for Pattern Recognition
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ICMCS
2007
IEEE
208views Multimedia» more  ICMCS 2007»
15 years 1 months ago
A Cognitive and Unsupervised Map Adaptation Approach to the Recognition of the Focus of Attention from Head Pose
In this paper, the recognition of the visual focus of attention (VFOA) of meeting participants (as defined by their eye gaze direction) from their head pose is addressed. To this ...
Jean-Marc Odobez, Sileye O. Ba
CVPR
2006
IEEE
15 years 11 months ago
Hidden Conditional Random Fields for Gesture Recognition
We introduce a discriminative hidden-state approach for the recognition of human gestures. Gesture sequences often have a complex underlying structure, and models that can incorpo...
Sy Bor Wang, Ariadna Quattoni, Louis-Philippe More...
ICPR
2006
IEEE
15 years 10 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
15 years 4 months ago
Primal sparse Max-margin Markov networks
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
Jun Zhu, Eric P. Xing, Bo Zhang
108
Voted
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 1 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing