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» A Generative Model Based Approach to Motion Segmentation
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ICIP
2003
IEEE
14 years 9 months ago
A probabilistic framework for image segmentation
A new probabilistic image segmentation model based on hypothesis testing and Gibbs Random Fields is introduced. First, a probabilistic difference measure derived from a set of hyp...
Slawo Wesolkowski, Paul W. Fieguth
TAMODIA
2004
13 years 9 months ago
Task models and interaction models in a multiple user interfaces generation process
In a Multiple User Interfaces (MUI) context, several models must be defined and adapted (tasks, user, .). Abstract models are progressively enriched in concrete models using patte...
Kinan Samaan, Franck Tarpin-Bernard
CLEF
2009
Springer
13 years 9 months ago
Unsupervised Word Decomposition with the Promodes Algorithm
We present Promodes, an algorithm for unsupervised word decomposition, which is based on a probabilistic generative model. The model considers segment boundaries as hidden variable...
Sebastian Spiegler, Bruno Golénia, Peter A....
AIPR
2002
IEEE
14 years 1 months ago
ICA Mixture Model based Unsupervised Classification of Hyperspectral Imagery
Conventional remote sensing classification techniques that model the data in each class with a multivariate Gaussian distribution are inefficient, as this assumption is generally ...
Chintan A. Shah, Manoj K. Arora, Stefan A. Robila,...
EMMCVPR
2009
Springer
14 years 16 hour ago
Reconstructing Optical Flow Fields by Motion Inpainting
An edge-sensitive variational approach for the restoration of optical flow fields is presented. Real world optical flow fields are frequently corrupted by noise, reflection artifac...
Benjamin Berkels, Claudia Kondermann, Christoph S....