|
|
The Publications
Result of the query in the list of publications :
245 Conference articles |
79 - Compression artifacts reduction using variational methods: algorithms and experimental study.
P. Weiss and L. Blanc-Féraud and T. Andre and M. Antonini. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Las Vegas, USA, March 2008.
Keywords : compression artifact, fast l1 optimization, Total variation, contrast enhancement, nesterov scheme, jpeg2000.
Copyright :
@INPROCEEDINGS{ICASSP_WEISS,
|
| author |
= |
{Weiss, P. and Blanc-Féraud, L. and Andre, T. and Antonini, M.}, |
| title |
= |
{Compression artifacts reduction using variational methods: algorithms and experimental study}, |
| year |
= |
{2008}, |
| month |
= |
{March}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Las Vegas, USA}, |
| url |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/Conferences/icassp2008.pdf}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2008_ICASSP_WEISS.pdf}, |
| keyword |
= |
{compression artifact, fast l1 optimization, Total variation, contrast enhancement, nesterov scheme, jpeg2000} |
| } |
|
80 - AUTOMATIC FLAMINGO DETECTION USING A MULTIPLE BIRTH AND DEATH PROCESS.
S. Descamps and X. Descombes and A. Béchet and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Las Vegas, USA, March 2008.
Copyright : copyright IEEE 2008
@INPROCEEDINGS{descamps08,
|
| author |
= |
{Descamps, S. and Descombes, X. and Béchet, A. and Zerubia, J.}, |
| title |
= |
{AUTOMATIC FLAMINGO DETECTION USING A MULTIPLE BIRTH AND DEATH PROCESS}, |
| year |
= |
{2008}, |
| month |
= |
{March}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Las Vegas, USA}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2008_descamps08.pdf}, |
| keyword |
= |
{} |
| } |
|
81 - SATELLITE IMAGE RECONSTRUCTION FROM AN IRREGULAR SAMPLING.
E. Bughin and L. Blanc-Féraud and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Las Vegas, USA, March 2008.
Keywords : Irregular sampling, Variational methods, Fourier analysis, Satellite imaging.
Copyright :
@INPROCEEDINGS{Bughin08,
|
| author |
= |
{Bughin, E. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{SATELLITE IMAGE RECONSTRUCTION FROM AN IRREGULAR SAMPLING}, |
| year |
= |
{2008}, |
| month |
= |
{March}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Las Vegas, USA}, |
| url |
= |
{http://hal.inria.fr/docs/00/27/89/19/PDF/bughinICASSP08.pdf}, |
| keyword |
= |
{Irregular sampling, Variational methods, Fourier analysis, Satellite imaging} |
| } |
|
82 - Mixing Geometric and Radiometric Features for Change Classification.
A. Fournier and X. Descombes and J. Zerubia. In Proc. SPIE Symposium on Electronic Imaging, San Jose, USA, January 2008.
Keywords : Change detection, directional Statistics, polygonal approximation, Classification.
Copyright : Copyright 2008 SPIE and IS&T. This paper was published in the proceedings of IS&T/SPIE 20th Annual Symposium on Electronic Imaging and is made available as an electronic reprint (preprint) with permission of SPIE and IS&T. 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{fournier_spie08,
|
| author |
= |
{Fournier, A. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Mixing Geometric and Radiometric Features for Change Classification}, |
| year |
= |
{2008}, |
| month |
= |
{January}, |
| booktitle |
= |
{Proc. SPIE Symposium on Electronic Imaging}, |
| address |
= |
{San Jose, USA}, |
| url |
= |
{http://hal.inria.fr/inria-00269853/fr/}, |
| keyword |
= |
{Change detection, directional Statistics, polygonal approximation, Classification} |
| } |
Abstract :
Most basic change detection algorithms use a pixel-based approach. Whereas such approach is quite well defined for monitoring important area changes (such as urban growth monitoring) in low resolution images, an object based approach seems more relevant when the change detection is specifically aimed toward targets (such as small buildings and vehicles). In this paper, we present an approach that mixes radiometric and geometric features to qualify the changed zones. The goal is to establish bounds (appearance, disappearance, substitution ...) between the detected changes and the underlying objects. We proceed by first clustering the change map (containing each pixel bitemporal radiosity) in different classes using the entropy-kmeans algorithm. Assuming that most man-made objects have a polygonal shape, a polygonal approximation algorithm is then used in order to characterize the resulting zone shapes. Hence allowing us to refine the primary rough classification, by integrating the polygon orientations in the state space. Tests are currently conducted on Quickbird data. |
|
83 - Diagramme de phase d'une énergie de type contours actifs d'ordre supérieur : le cas d'une barre longue.
A. El Ghoul and I. H. Jermyn and J. Zerubia. In 16ème congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle (RFIA), Amiens, France, January 2008.
Keywords : Diagramme de phase, Contours actifs d'ordre supérieur, Shape, geometric prior, Télédétection.
@INPROCEEDINGS{ElGhoul08,
|
| author |
= |
{El Ghoul, A. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Diagramme de phase d'une énergie de type contours actifs d'ordre supérieur : le cas d'une barre longue}, |
| year |
= |
{2008}, |
| month |
= |
{January}, |
| booktitle |
= |
{16ème congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle (RFIA)}, |
| address |
= |
{Amiens, France}, |
| url |
= |
{https://hal.inria.fr/inria-00319575}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/31/95/75/PDF/rfia08aymenelghoul.pdf}, |
| keyword |
= |
{Diagramme de phase, Contours actifs d'ordre supérieur, Shape, geometric prior, Télédétection} |
| } |
Résumé :
Dans cet article, nous présentons l’analyse de stabilité du modèle des “contours actifs d’ordre supérieur” (CAOS), pour l’extraction des réseaux routiers présents dans des images de télédétection. Le modèle énergétique des CAOS à minimiser présente des comportements différents en fonction des valeurs des paramètres du modèle.
Il s’est avéré que deux structures géométriques sont favorisées
par ce modèle : des structures linéiques et circulaires. Nous nous intéressons ici à la détermination du diagramme de phase, qui définit les gammes des valeurs des paramètres du modèle des CAOS, permettant d’obtenir des structures linéiques. |
Abstract :
In this paper, we present a stability analysis of a “higher-order active contour” (HOAC) model for road network extraction from remotely sensed images. The HOAC energy presents several different behaviours depending on the model parameter values. Two types of geometric structure are favoured, namely line networks and circles. In this
work, we derive the phase diagram giving the parameter ranges of the HOAC model that allow stable linear structures. |
|
84 - Forest Fire Detection based on Gaussian field analysis.
F. Lafarge and X. Descombes and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), Poznan, Poland, September 2007.
Note : Copyright EURASIP
Keywords : Gaussian Field, DT-caracteristic, Forest fires.
@INPROCEEDINGS{lafarge_eusipco07,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Forest Fire Detection based on Gaussian field analysis}, |
| year |
= |
{2007}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{Poznan, Poland}, |
| note |
= |
{Copyright EURASIP}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_lafarge_eusipco07.pdf}, |
| keyword |
= |
{Gaussian Field, DT-caracteristic, Forest fires} |
| } |
|
85 - 3D city modeling based on Hidden Markov Model.
F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. In Proc. IEEE International Conference on Image Processing (ICIP), San Antonio, U.S., September 2007.
Note : Copyright IEEE
Keywords : 3D reconstruction, Building, Hidden Markov Model.
@INPROCEEDINGS{lafarge_icip07,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
| title |
= |
{3D city modeling based on Hidden Markov Model}, |
| year |
= |
{2007}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{San Antonio, U.S.}, |
| note |
= |
{Copyright IEEE}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4379207}, |
| keyword |
= |
{3D reconstruction, Building, Hidden Markov Model} |
| } |
|
86 - A `Gas of Circles' Phase Field Model and its Application to Tree Crown Extraction.
P. Horvath and I. H. Jermyn. In Proc. European Signal Processing Conference (EUSIPCO), Poznan, Poland, September 2007.
Keywords : Phase Field, Tree Crown Extraction.
@INPROCEEDINGS{Horvath07d,
|
| author |
= |
{Horvath, P. and Jermyn, I. H.}, |
| title |
= |
{A `Gas of Circles' Phase Field Model and its Application to Tree Crown Extraction}, |
| year |
= |
{2007}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{Poznan, Poland}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Horvath07d.pdf}, |
| keyword |
= |
{Phase Field, Tree Crown Extraction} |
| } |
Abstract :
The problem of extracting the region in the image domain
corresponding to an a priori unknown number of circular objects
occurs in several domains. We propose a new model of a `gas of
circles', the ensemble of regions in the image domain composed of
circles of a given radius. The model uses the phase field
reformulation of higher-order active contours (HOACs). Phase fields
possess several advantages over contour and level set approaches to
region modelling, in particular for HOAC models. The reformulation
allows us to benefit from these advantages without losing the
strengths of the HOAC framework. Combined with a suitable likelihood
energy, and applied to the tree crown extraction problem, the new
model shows markedly improved performance, both in quality of
results and in computation time, which is two orders of magnitude
less than the HOAC level set implementation.
|
|
87 - A Phase Field Model Incorporating Generic and Specific Prior Knowledge Applied to Road Network Extraction from VHR Satellite Images.
T. Peng and I. H. Jermyn and V. Prinet and J. Zerubia and B. Hu. In Proc. British Machine Vision Conference (BMVC), Warwick, UK, September 2007.
Keywords : Road network, Very high resolution, Higher-order, Active contour, Shape, Prior.
@INPROCEEDINGS{Peng07a,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J. and Hu, B.}, |
| title |
= |
{A Phase Field Model Incorporating Generic and Specific Prior Knowledge Applied to Road Network Extraction from VHR Satellite Images}, |
| year |
= |
{2007}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. British Machine Vision Conference (BMVC)}, |
| address |
= |
{Warwick, UK}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Peng07a.pdf}, |
| keyword |
= |
{Road network, Very high resolution, Higher-order, Active contour, Shape, Prior} |
| } |
Abstract :
We address the problem of updating road maps in dense urban areas by extracting the main road network from a very high resolution (VHR) satellite image. Our model of the region occupied by the road network in the image is innovative. It incorporates three different types of prior geometric knowledge: generic boundary smoothness constraints, equivalent to a standard active contour prior; knowledge of the geometric properties of road networks (i.e. that they occupy regions composed of long, low-curvature segments joined at junctions), equivalent to a higher-order active contour prior; and knowledge of the road network at an earlier date derived from GIS data, similar to other ‘shape priors’ in the literature. In addition, we represent the road network region as a ‘phase field’, which offers a number of important advantages over other region modelling frameworks. All three types of prior knowledge prove important for overcoming the complexity of geometric ‘noise’ in VHR images. Promising results and a comparison with several other techniques demonstrate the effectiveness of our approach. |
|
88 - Apprentissage non supervisé des SVM par un algorithme des K-moyennes entropique pour la détection de zones brûlées.
O. Zammit and X. Descombes and J. Zerubia. In Proc. GRETSI Symposium on Signal and Image Processing, Troyes, France, September 2007.
Keywords : Satellite images, Forest fires, Burnt areas, Classification, Support Vector Machines, Learning base.
@INPROCEEDINGS{zammit_gretsi_07,
|
| author |
= |
{Zammit, O. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Apprentissage non supervisé des SVM par un algorithme des K-moyennes entropique pour la détection de zones brûlées}, |
| year |
= |
{2007}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. GRETSI Symposium on Signal and Image Processing}, |
| address |
= |
{Troyes, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_zammit_gretsi_07.pdf}, |
| keyword |
= |
{Satellite images, Forest fires, Burnt areas, Classification, Support Vector Machines, Learning base} |
| } |
|
 top of the page
These pages were generated by 
|
2011 Activity report
get the bibtex
