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» Recognition Model with Extension Fields
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CVPR
2006
IEEE
14 years 9 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...
CVPR
2009
IEEE
15 years 2 months ago
Max-Margin Hidden Conditional Random Fields for Human Action Recognition
We present a new method for classification with structured latent variables. Our model is formulated using the max-margin formalism in the discriminative learning literature. We...
Yang Wang 0003, Greg Mori
ICPR
2004
IEEE
14 years 8 months ago
A Hybrid Face Recognition Method using Markov Random Fields
We propose a hybrid face recognition method that combines holistic and feature analysis-based approaches using a Markov random field (MRF) model. The face images are divided into ...
Dimitris N. Metaxas, Rui Huang, Vladimir Pavlovic
ISCI
2010
134views more  ISCI 2010»
13 years 5 months ago
Cascade Markov random fields for stroke extraction of Chinese characters
Extracting perceptually meaningful strokes plays an essential role in modeling structures of handwritten Chinese characters for accurate character recognition. This paper proposes...
Jia Zeng, Wei Feng, Lei Xie, Zhi-Qiang Liu
IJCV
2008
241views more  IJCV 2008»
13 years 7 months ago
Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields
We investigate the role of sparsity and localized features in a biologically-inspired model of visual object classification. As in the model of Serre, Wolf, and Poggio, we first a...
Jim Mutch, David G. Lowe