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» A Revisit of Generative Model for Automatic Image Annotation...
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CVPR
2009
IEEE
14 years 11 months ago
A Revisit of Generative Model for Automatic Image Annotation using Markov Random Fields
Much research effort on Automatic Image Annotation (AIA) has been focused on Generative Model, due to its well formed theory and competitive performance as compared with many we...
Yu Xiang (Fudan University), Xiangdong Zhou (Fudan...
PSIVT
2007
Springer
170views Multimedia» more  PSIVT 2007»
13 years 10 months ago
Markov Random Fields and Spatial Information to Improve Automatic Image Annotation
Content-based image retrieval (CBIR) is currently limited because of the lack of representational power of the low-level image features, which fail to properly represent the actual...
Carlos Hernández-Gracidas, Luis Enrique Suc...
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,...
ICASSP
2011
IEEE
12 years 8 months ago
A new stochastic image model based on Markov random fields and its application to texture modeling
Stochastic image modeling based on conventional Markov random fields is extensively discussed in the literature. A new stochastic image model based on Markov random fields is intr...
Siamak Yousefi, Nasser D. Kehtarnavaz
CVPR
2010
IEEE
13 years 10 months ago
Semantic Context Modeling with Maximal Margin Conditional Random Fields for Automatic Image Annotation
Context modeling for Vision Recognition and Automatic Image Annotation (AIA) has attracted increasing attentions in recent years. For various contextual information and resources,...
Yu Xiang, Xiangdong Zhou, Zuotao Liu, Tat-seng chu...