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» Hidden Conditional Random Fields for Gesture Recognition
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AAAI
2008
13 years 10 months ago
Hidden Dynamic Probabilistic Models for Labeling Sequence Data
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
Xiaofeng Yu, Wai Lam
NAACL
2010
13 years 5 months ago
Investigations into the Crandem Approach to Word Recognition
We suggest improvements to a previously proposed framework for integrating Conditional Random Fields and Hidden Markov Models, dubbed a Crandem system (2009). The previous authors...
Rohit Prabhavalkar, Preethi Jyothi, William Hartma...
NIPS
2008
13 years 9 months ago
Learning a discriminative hidden part model for human action recognition
We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden conditi...
Yang Wang 0003, Greg Mori
PAMI
2010
207views more  PAMI 2010»
13 years 2 months ago
Document Ink Bleed-Through Removal with Two Hidden Markov Random Fields and a Single Observation Field
We present a new method for blind document bleed through removal based on separate Markov Random Field (MRF) regularization for the recto and for the verso side, where separate pri...
Christian Wolf
ICPR
2000
IEEE
14 years 4 days ago
Hidden Markov Random Field Based Approach for Off-Line Handwritten Chinese Character Recognition
This paper presents a Hidden Markov Mesh Random Field (HMMRF) based approach for off-line handwritten Chinese characters recognition using statistical observation sequences embedd...
Qing Wang, Rongchun Zhao, Zheru Chi, David Dagan F...