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Publications of 2007
Result of the query in the list of publications :
28 Conference articles |
22 - Gap Filling in 3D Vessel like Patterns with Tensor Fields.
L. Risser and F. Plouraboue and X. Descombes. In Proc. International Conference on Computer Vision Theory
and Applications, 2007.
Keywords : tensor voting, vascular network.
@INPROCEEDINGS{XDbarca1,
|
| author |
= |
{Risser, L. and Plouraboue, F. and Descombes, X.}, |
| title |
= |
{Gap Filling in 3D Vessel like Patterns with Tensor Fields}, |
| year |
= |
{2007}, |
| booktitle |
= |
{Proc. International Conference on Computer Vision Theory
and Applications}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_XDbarca1.pdf}, |
| keyword |
= |
{tensor voting, vascular network} |
| } |
|
23 - Wavelet-based restoration methods: application to 3D confocal microscopy images.
C. Chaux and L. Blanc-Féraud and J. Zerubia. In Proc. SPIE Conference on Wavelets, 2007.
Keywords : Restoration, Deconvolution, 3D images, Confocal microscopy, Poisson noise, Wavelets.
Copyright : Copyright 2007 Society of Photo-Optical Instrumentation Engineers.
This paper was published in Proc. SPIE Conference on Wavelets and is made available as an electronic reprint (preprint) with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
@INPROCEEDINGS{chaux2007,
|
| author |
= |
{Chaux, C. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{Wavelet-based restoration methods: application to 3D confocal microscopy images}, |
| year |
= |
{2007}, |
| booktitle |
= |
{Proc. SPIE Conference on Wavelets}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_chaux2007.pdf}, |
| keyword |
= |
{Restoration, Deconvolution, 3D images, Confocal microscopy, Poisson noise, Wavelets} |
| } |
|
24 - Detection and Completion of Filaments: A Vector Field and PDE Approach.
A. Baudour and G. Aubert and L. Blanc-Féraud. In SSVM 2007, LNCS 4485 proceedings, 2007.
@INPROCEEDINGS{ssvm2007,
|
| author |
= |
{Baudour, A. and Aubert, G. and Blanc-Féraud, L.}, |
| title |
= |
{Detection and Completion of Filaments: A Vector Field and PDE Approach}, |
| year |
= |
{2007}, |
| booktitle |
= |
{ SSVM 2007, LNCS 4485 proceedings}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_ssvm2007.pdf}, |
| keyword |
= |
{} |
| } |
|
25 - Détection et Complétion de Filaments: une approche variationelle et vectorielle.
A. Baudour and G. Aubert and L. Blanc-Féraud. In Colloque Gretsi Troyes, 2007, 2007.
@INPROCEEDINGS{ Gretsi 2007,
|
| author |
= |
{Baudour, A. and Aubert, G. and Blanc-Féraud, L.}, |
| title |
= |
{Détection et Complétion de Filaments: une approche variationelle et vectorielle}, |
| year |
= |
{2007}, |
| booktitle |
= |
{Colloque Gretsi Troyes, 2007}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_ Gretsi 2007.pdf}, |
| keyword |
= |
{} |
| } |
|
26 - Vers une détection et une classification non-supervisées des changements inter-images.
A. Fournier and X. Descombes and J. Zerubia. In Proc. Traitement et Analyse de l'Information - Méthodes et Applications (TAIMA), 2007.
Keywords : Markov Random Fields, Registration, Change detection, Clustering.
@INPROCEEDINGS{fournier-taima-07,
|
| author |
= |
{Fournier, A. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Vers une détection et une classification non-supervisées des changements inter-images}, |
| year |
= |
{2007}, |
| booktitle |
= |
{Proc. Traitement et Analyse de l'Information - Méthodes et Applications (TAIMA)}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_fournier-taima-07.pdf}, |
| keyword |
= |
{Markov Random Fields, Registration, Change detection, Clustering} |
| } |
|
27 - Use of ant colony
optimization for finding neighbourhoods in non-stationary Markov random
field models.
S. Le Hegarat-Mascle and A. Kallel and X. Descombes. In Pattern Recognition and Machine Intelligence (PReMI'07), 2007.
Keywords : Ants colonization, Markov Random Fields.
@INPROCEEDINGS{ant07b,
|
| author |
= |
{Le Hegarat-Mascle, S. and Kallel, A. and Descombes, X.}, |
| title |
= |
{Use of ant colony
optimization for finding neighbourhoods in non-stationary Markov random
field models}, |
| year |
= |
{2007}, |
| booktitle |
= |
{Pattern Recognition and Machine Intelligence (PReMI'07)}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_ant07b.pdf}, |
| keyword |
= |
{Ants colonization, Markov Random Fields} |
| } |
|
28 - Tree Species Classification Using Radiometry, Texture and Shape Based Features.
M. S. Kulikova and M. Mani and A. Srivastava and X. Descombes and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), 2007.
Keywords : shape based features, SVM, tree classification.
@INPROCEEDINGS{Kulikova07,
|
| author |
= |
{Kulikova, M. S. and Mani, M. and Srivastava, A. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Tree Species Classification Using Radiometry, Texture and Shape Based Features}, |
| year |
= |
{2007}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| pdf |
= |
{http://hal.archives-ouvertes.fr/docs/00/46/55/05/PDF/Kulikova_EUSIPCO2007.pdf}, |
| keyword |
= |
{shape based features, SVM, tree classification} |
| } |
Abstract :
We consider the problem of tree species classification from high resolution aerial images based on radiometry, texture and a shape modeling. We use the notion of shape space proposed by Klassen et al., which provides a shape description invariant to translation, rotation and scaling. The shape features are extracted within a geodesic distance in the shape space. We then perform a classification using a SVM approach. We are able to show that the shape descriptors improve the classification performance relative to a classifier based on radiometric and textural descriptors alone. We obtain these results using high resolution Colour InfraRed (CIR) aerial images provided by the Swedish University of Agricultural Sciences. The image viewpoint is close to the nadir, i.e. the tree crowns are seen from above. |
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6 Technical and Research Reports |
1 - Support Vector Machines for burnt area discrimination.
O. Zammit and X. Descombes and J. Zerubia. Research Report 6343, INRIA, November 2007.
Keywords : Forest fires, Burnt areas, Satellite images, Support Vector Machines, Classification.
@TECHREPORT{zammit_RR_07,
|
| author |
= |
{Zammit, O. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Support Vector Machines for burnt area discrimination}, |
| year |
= |
{2007}, |
| month |
= |
{November}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{6343}, |
| url |
= |
{http://hal.inria.fr/inria-00185101/fr/}, |
| pdf |
= |
{http://hal.inria.fr/inria-00185101/fr/}, |
| keyword |
= |
{Forest fires, Burnt areas, Satellite images, Support Vector Machines, Classification} |
| } |
Résumé :
Ce rapport aborde le problème de l'évaluation des dégâts après un feux de forêt. La détection est effectuée à partir d'une seule image satellite (SPOT 5) acquise après le feu. Afin de détecter les zones brûlées, nous utilisons une approche récente de classification nommée SVM (Séparateurs à Vaste Marge). Cette méthode est comparée aux algorithmes de classification plus conventionnels comme les K-moyennes ou les K-plus proches voisins, qui sont régulièrement utilisés en traitement d'image. Nous proposons également une méthode de classification non supervisée combinant les K-moyennes et les SVM. Les résultats fournis par les différentes techniques sont comparés à des vérités de terrain sur diverses zones brûlées. |
Abstract :
This report addresses the problem of burnt area discrimination using remote sensing images. The detection is based on a single post-fire image acquired by SPOT 5 satellite. To delineate the burnt areas, we use a recent classification method called Support Vectors Machines (SVM). This approach is compared to more conventional classifiers such as K-means or K-nearest neighbours which are widely used in image processing. We also proposed a new automatic classification approach combining K-means and SVM. The results given by the different methods are finally compared to ground truths on various burnt areas |
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2 - Détection de flamants roses par processus ponctuels marqués pour l'estimation de la taille des populations.
S. Descamps and X. Descombes and A. Béchet and J. Zerubia. Research Report 6328, INRIA, October 2007.
Keywords : Object extraction, modélisation stochastique , Marked point process, dynamique de naissance/mort, environnement, flamants roses.
@TECHREPORT{Descamps-Descombes,
|
| author |
= |
{Descamps, S. and Descombes, X. and Béchet, A. and Zerubia, J.}, |
| title |
= |
{Détection de flamants roses par processus ponctuels marqués pour l'estimation de la taille des populations}, |
| year |
= |
{2007}, |
| month |
= |
{October}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{6328}, |
| url |
= |
{http://hal.inria.fr/inria-00180811}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/18/08/93/PDF/RR-Desc-Desc-Bech-Zeru.pdf}, |
| keyword |
= |
{Object extraction, modélisation stochastique , Marked point process, dynamique de naissance/mort, environnement, flamants roses} |
| } |
|
3 - An adaptive simulated annealing cooling schedule for object detection in images.
M. Ortner and X. Descombes and J. Zerubia. Research Report 6336, INRIA, October 2007.
Keywords : Image procressing, Shape extraction, Spatial point process, Simulated Annealing, Adaptive cooling schedule.
@TECHREPORT{Ortner-Descombes,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{An adaptive simulated annealing cooling schedule for object detection in images}, |
| year |
= |
{2007}, |
| month |
= |
{October}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{6336}, |
| url |
= |
{https://hal.inria.fr/inria-00181764}, |
| pdf |
= |
{https://hal.inria.fr/inria-00181764}, |
| keyword |
= |
{Image procressing, Shape extraction, Spatial point process, Simulated Annealing, Adaptive cooling schedule} |
| } |
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