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ICPR
2002
IEEE
14 years 5 months ago
Face Detection and Synthesis Using Markov Random Field Models
Markov Random Fields (MRFs) are proposed as viable stochastic models for the spatial distribution of gray level intensities for images of human faces. These models are trained usi...
Sarat C. Dass, Anil K. Jain, Xiaoguang Lu
FGR
2008
IEEE
346views Biometrics» more  FGR 2008»
13 years 11 months ago
Markov random field models for hair and face segmentation
This paper presents an algorithm for measuring hair and face appearance in 2D images. Our approach starts by using learned mixture models of color and location information to sugg...
Kuang-chih Lee, Dragomir Anguelov, Baris Sumengen,...
ICCV
2001
IEEE
14 years 6 months ago
Markov Face Models
The spatial distribution of gray level intensities in an image can be naturally modeled using Markov Random Field (MRF) models. We develop and investigate the performance of face ...
Sarat C. Dass, Anil K. Jain
TIP
1998
124views more  TIP 1998»
13 years 4 months ago
Texture synthesis via a noncausal nonparametric multiscale Markov random field
Abstract— Our noncausal, nonparametric, multiscale, Markov random field (MRF) model is capable of synthesising and capturing the characteristics of a wide variety of textures, f...
Rupert Paget, I. Dennis Longstaff
ICPR
2004
IEEE
14 years 5 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