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» 2D Shape Recognition by Hidden Markov Models
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ICPR
2006
IEEE
16 years 3 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...
130
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CVIU
2006
317views more  CVIU 2006»
15 years 1 months ago
A general method for human activity recognition in video
In this paper we develop a system for human behaviour recognition in video sequences. Human behaviour is modelled as a stochastic sequence of actions. Actions are described by a f...
Neil Robertson, Ian D. Reid
ICIP
2002
IEEE
16 years 3 months ago
Parametric contour tracking using unscented Kalman filter
This paper presents an efficient method to integrate various spatial-temporal constraints to regularize the contour tracking. The global shape of the contour is represented in a p...
Yunqiang Chen, Thomas S. Huang, Yong Rui
ICIP
2008
IEEE
16 years 3 months ago
Robust snake convergence based on dynamic programming
The extraction of contours using deformable models, such as snakes, is a problem of great interest in computer vision, particular in areas of medical imaging and tracking. Snakes ...
Akshaya Kumar Mishra, Paul W. Fieguth, David A. Cl...
CVPR
1998
IEEE
16 years 3 months ago
Action Recognition Using Probabilistic Parsing
A new approach to the recognition of temporal behaviors and activities is presented. The fundamental idea, inspired by work in speech recognition, is to divide the inference probl...
Aaron F. Bobick, Yuri A. Ivanov