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» A Generative Model Based Approach to Motion Segmentation
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137
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ICIP
2003
IEEE
16 years 4 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
15 years 3 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
111
Voted
CLEF
2009
Springer
15 years 3 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....
146
Voted
AIPR
2002
IEEE
15 years 7 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
15 years 6 months 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....