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» Markov Random Field Modeling in Computer Vision
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ICPR
2006
IEEE
14 years 10 months ago
A maximum margin discriminative learning algorithm for temporal signals
We propose a new maximum margin discriminative learning algorithm here for classification of temporal signals. It is superior to conventional HMM in the sense that it does not nee...
Wenjie Xu, Jiankang Wu, Zhiyong Huang
ICPR
2010
IEEE
14 years 4 months ago
Typographical Features for Scene Text Recognition
Scene text images feature an abundance of font style variety but a dearth of data in any given query. Recognition methods must be robust to this variety or adapt to the query data...
Jerod Weinman
ICPR
2008
IEEE
14 years 3 months ago
A new HMM for on-line character recognition using pen-direction and pen-coordinate features
A new hidden Markov model (HMM) is proposed for on-line character recognition using two typical features, pen-direction feature and pen-coordinate feature. These two features are ...
Yoshinori Katayama, Seiichi Uchida, Hiroaki Sakoe
ICPR
2008
IEEE
14 years 3 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
ICCV
1998
IEEE
14 years 11 months ago
Ego-Motion and Omnidirectional Cameras
Recent research in image sensors has produced cameras with very large fields of view. A n area of computer vision research which will benefit from this technology is the computati...
Joshua Gluckman, Shree K. Nayar