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Publications sur fast optimization
Résultat de la recherche dans la liste des publications :
2 Articles |
1 - Geometric Feature Extraction by a Multi-Marked Point Process .
F. Lafarge et G. Gimel'farb et X. Descombes. IEEE Trans. Pattern Analysis and Machine Intelligence, 32(9): pages 1597-1609, septembre 2010.
Mots-clés : Shape extraction, Spatial point process, Geometrie stochastique, fast optimization, Texture, remote sensing.
@ARTICLE{pami09b_lafarge,
|
| author |
= |
{Lafarge, F. and Gimel'farb, G. and Descombes, X.}, |
| title |
= |
{Geometric Feature Extraction by a Multi-Marked Point Process }, |
| year |
= |
{2010}, |
| month |
= |
{septembre}, |
| journal |
= |
{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
| volume |
= |
{32}, |
| number |
= |
{9}, |
| pages |
= |
{1597-1609}, |
| url |
= |
{http://dx.doi.org/10.1109/TPAMI.2009.152}, |
| keyword |
= |
{Shape extraction, Spatial point process, Geometrie stochastique, fast optimization, Texture, remote sensing} |
| } |
Abstract :
This paper presents a new stochastic marked point process for describing images in terms of a finite library of geometric objects. Image analysis based on conventional marked point processes has already produced convincing results but at the expense of parameter tuning, computing time, and model specificity. Our more general multimarked point process has simpler parametric setting, yields notably shorter computing times, and can be applied to a variety of applications. Both linear and areal primitives extracted from a library of geometric objects are matched to a given image using a probabilistic Gibbs model, and a Jump-Diffusion process is performed to search for the optimal object configuration. Experiments with remotely sensed images and natural textures show that the proposed approach has good potential. We conclude with a discussion about the insertion of more complex object interactions in the model by studying the compromise between model complexity and efficiency. |
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2 - Efficient schemes for total variation minimization under constraints in image processing.
P. Weiss et L. Blanc-Féraud et G. Aubert. SIAM journal on Scientific Computing, 31(3): pages 2047-2080, 2009.
Mots-clés : Variation totale, l1 norm, nesterov scheme, Rudin Osher Fatemi, fast optimization, real time.
Copyright : Copyright Siam Society for Industrial and Applied
@ARTICLE{SIAM_JSC_PWEISS,
|
| author |
= |
{Weiss, P. and Blanc-Féraud, L. and Aubert, G.}, |
| title |
= |
{Efficient schemes for total variation minimization under constraints in image processing}, |
| year |
= |
{2009}, |
| journal |
= |
{SIAM journal on Scientific Computing}, |
| volume |
= |
{31}, |
| number |
= |
{3}, |
| pages |
= |
{2047-2080}, |
| url |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/SIAM_JSC09_PWEISS.pdf}, |
| pdf |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/SIAM_JSC09_PWEISS.pdf}, |
| keyword |
= |
{Variation totale, l1 norm, nesterov scheme, Rudin Osher Fatemi, fast optimization, real time} |
| } |
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