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ICML
2003
IEEE
14 years 5 months ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
AR
2007
204views more  AR 2007»
13 years 5 months ago
Action recognition and understanding through motor primitives
In robotics, recognition of human activity has been used extensively for robot task learning through imitation and demonstration. However, there has not been much work on modeling...
Isabel Serrano Vicente, Ville Kyrki, Danica Kragic...
ICPR
2006
IEEE
14 years 6 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...
ICMCS
2006
IEEE
128views Multimedia» more  ICMCS 2006»
13 years 11 months ago
Efficient Recognition of Authentic Dynamic Facial Expressions on the Feedtum Database
In order to allow for fast recognition of a user’s affective state we discuss innovative holistic and self organizing approaches for efficient facial expression analysis. The f...
Frank Wallhoff, Björn Schuller, Michael Hawel...
ICPR
2010
IEEE
13 years 12 months ago
Exploiting Visual Quasi-Periodicity for Automated Chewing Event Detection Using Active Appearance Models and Support Vector Mach
We present a method that automatically detects chewing events in surveillance video of a subject. Firstly, an Active Appearance Model (AAM) is used to track a subject’s face acr...
Steven Cadavid, Mohamed Abdel-Mottaleb