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» Markov Random Field Modeling in Computer Vision
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CVPR
2008
IEEE
14 years 11 months ago
Latent topic random fields: Learning using a taxonomy of labels
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Xuming He, Richard S. Zemel
ICML
2007
IEEE
14 years 9 months ago
Dynamic hierarchical Markov random fields and their application to web data extraction
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
CVPR
2004
IEEE
14 years 11 months ago
Automatic View Recognition in Echocardiogram Videos Using Parts-Based Representation
Indexing echocardiogram videos at different levels of structure is essential for providing efficient access to their content for browsing and retrieval purposes. We present a nove...
Shahram Ebadollahi, Shih-Fu Chang, Henry Wu
CVPR
2007
IEEE
14 years 11 months ago
Cast Shadow Removal Combining Local and Global Features
In this paper, we present a method using pixel-level information, local region-level information and global-level information to remove shadow. At the pixel-level, we employ GMM t...
Zhou Liu, Kaiqi Huang, Tieniu Tan, Liangsheng Wang
CVPR
2011
IEEE
13 years 5 months ago
Global Stereo Matching Leveraged by Sparse Ground Control Points
We present a novel global stereo model that makes use of constraints from points with known depths, i.e., the Ground Control Points (GCPs) as referred to in stereo literature. Our...
Liang Wang, Ruigang Yang