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» Modeling Image Textures by Gibbs Random Fields
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ISVC
2010
Springer
14 years 11 months ago
Markov Random Field-Based Clustering for the Integration of Multi-view Range Images
Abstract. Multi-view range image integration aims at producing a single reasonable 3D point cloud. The point cloud is likely to be inconsistent with the measurements topologically ...
Ran Song, Yonghuai Liu, Ralph R. Martin, Paul L. R...
ECCV
2008
Springer
16 years 2 months ago
Sparse Long-Range Random Field and Its Application to Image Denoising
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
Yunpeng Li, Daniel P. Huttenlocher
MICCAI
2007
Springer
16 years 1 months ago
Object Localization Based on Markov Random Fields and Symmetry Interest Points
We present an approach to detect anatomical structures by configurations of interest points, from a single example image. The representation of the configuration is based on Markov...
Branislav Micusík, Georg Langs, Horst Bisch...
105
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ICIP
2010
IEEE
14 years 10 months ago
Fast semantic scene segmentation with conditional random field
In this paper, we present a fast approach to obtain semantic scene segmentation with high precision. We employ a two-stage classifier to label all image pixels. First, we use the ...
Wen Yang, Dengxin Dai, Bill Triggs, Gui-Song Xia, ...
NIPS
2004
15 years 1 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...