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» Graph Cut based Inference with Co-occurrence Statistics
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LREC
2010
197views Education» more  LREC 2010»
13 years 5 months ago
Automatic Annotation of Co-Occurrence Relations
We introduce a method for automatically labelling edges of word co-occurrence graphs with semantic relations. Therefore we only make use of training data already contained within ...
Dirk Goldhahn, Uwe Quasthoff
ECCV
2010
Springer
13 years 9 months ago
Graph Cut based Inference with Co-occurrence Statistics
Abstract. Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as this is computationally tractable. In t...
ICPR
2008
IEEE
13 years 10 months ago
Graph cut based deformable model with statistical shape priors
This paper presents a novel graph cut based segmentation approach with shape priors. The model incorporates statistical shape prior information with the active contour without edg...
Noha Youssry El-Zehiry, Adel Elmaghraby
ECCV
2006
Springer
14 years 5 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady
CVPR
2012
IEEE
11 years 6 months ago
Graph cuts optimization for multi-limb human segmentation in depth maps
We present a generic framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs in depth maps...
Antonio Hernández-Vela, Nadezhda Zlateva, A...