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» A probabilistic framework for image segmentation
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ICCV
2011
IEEE
12 years 8 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
DAGM
2003
Springer
14 years 1 months ago
A Generative Model Based Approach to Motion Segmentation
We address the question of how to choose between different likelihood functions for motion estimation. To this end, we formulate motion estimation as a problem of Bayesian inferen...
Daniel Cremers, Alan L. Yuille
IJCV
2000
164views more  IJCV 2000»
13 years 7 months ago
Probabilistic Modeling and Recognition of 3-D Objects
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
Joachim Hornegger, Heinrich Niemann
ICPR
2006
IEEE
14 years 9 months ago
Texture Segmentation Using Independent Component Analysis of Gabor Features
This paper proposes a novel method for texture segmentation using independent component analysis (ICA) of Gabor features (called ICAG). It has three distinguished aspects. (1) Gab...
Yang Chen, Runsheng Wang
ICCV
2003
IEEE
14 years 1 months ago
Dynamic Texture Segmentation
We address the problem of segmenting a sequence of images of natural scenes into disjoint regions that are characterized by constant spatio-temporal statistics. We model the spati...
Gianfranco Doretto, Daniel Cremers, Paolo Favaro, ...