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The Publications
Result of the query in the list of publications :
245 Conference articles |
99 - Indexing Satellite Images with Features Computed from Man-Made Structures on the Earth’s Surface.
A. Bhattacharya and M. Roux and H. Maitre and I. H. Jermyn and X. Descombes and J. Zerubia. In Proc. International Workshop on Content-Based Multimedia Indexing, Bordeaux, France, June 2007.
Keywords : Indexation, Road network, Semantic, Retrieval, Feature statistics.
@INPROCEEDINGS{Bhattacharya07a,
|
| author |
= |
{Bhattacharya, A. and Roux, M. and Maitre, H. and Jermyn, I. H. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Indexing Satellite Images with Features Computed from Man-Made Structures on the Earth’s Surface}, |
| year |
= |
{2007}, |
| month |
= |
{June}, |
| booktitle |
= |
{Proc. International Workshop on Content-Based Multimedia Indexing}, |
| address |
= |
{Bordeaux, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Bhattacharya07a.pdf}, |
| keyword |
= |
{Indexation, Road network, Semantic, Retrieval, Feature statistics} |
| } |
Abstract :
Indexing and retrieval from remote sensing image databases relies on the extraction of appropriate information from the data about the entity of interest (e.g. land cover type) and on the robustness of this extraction to nuisance variables. Other entities in an image may be strongly correlated with the entity of interest and their properties can therefore be used to characterize this entity. The road network contained in an image is one example. The properties of road networks vary considerably from one geographical environment to another, and they can therefore be used to classify and retrieve such environments. In this paper, we define several such environments, and classify them with the aid of geometrical and topological features computed from the road networks occurring in them. The relative failure of network extraction methods in certain types of urban area obliges us to segment such areas and to add a second set of geometrical and topological features computed from the segmentations. To validate the approach, feature selection and SVM linear kernel classification are performed on the feature set arising from a diverse image database. |
|
100 - Riemannian Analysis of Probability Density Functions with Applications in Vision.
S. Joshi and A. Srivastava and I. H. Jermyn. In Proc. IEEE Computer Vision and Pattern Recognition (CVPR), Minneapolis, USA, June 2007.
Keywords : Probability density function, Metric, Geodesic, Reparameterization.
@INPROCEEDINGS{Joshi07,
|
| author |
= |
{Joshi, S. and Srivastava, A. and Jermyn, I. H.}, |
| title |
= |
{Riemannian Analysis of Probability Density Functions with Applications in Vision}, |
| year |
= |
{2007}, |
| month |
= |
{June}, |
| booktitle |
= |
{Proc. IEEE Computer Vision and Pattern Recognition (CVPR)}, |
| address |
= |
{Minneapolis, USA}, |
| url |
= |
{http://dx.doi.org/10.1109/CVPR.2007.383188 }, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Joshi07.pdf}, |
| keyword |
= |
{Probability density function, Metric, Geodesic, Reparameterization} |
| } |
Abstract :
Applications in computer vision involve statistically analyzing an important class of constrained, non- negative functions, including probability density functions (in texture analysis), dynamic time-warping functions (in activity analysis), and re-parametrization or non-rigid registration functions (in shape analysis of curves). For this one needs to impose a Riemannian structure on the spaces formed by these functions. We propose a em spherical version of the Fisher-Rao metric that provides closed form expressions for geodesics and distances, and allows an efficient computation of statistics. We compare this metric with some previously used metrics and present an application in planar shape classification. |
|
101 - A Hierarchical finite-state model for texture segmentation.
G. Scarpa and M. Haindl and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vol. 1, pages 1209-1212, Honolulu, HI (USA), April 2007.
@INPROCEEDINGS{scarpa_icassp_07,
|
| author |
= |
{Scarpa, G. and Haindl, M. and Zerubia, J.}, |
| title |
= |
{A Hierarchical finite-state model for texture segmentation}, |
| year |
= |
{2007}, |
| month |
= |
{April}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| volume |
= |
{1}, |
| pages |
= |
{1209-1212}, |
| address |
= |
{Honolulu, HI (USA)}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4217303}, |
| keyword |
= |
{} |
| } |
|
102 - Urban road extraction from VHR images using a multiscale image model and a phase field model of network geometry.
T. Peng and I. H. Jermyn and V. Prinet and J. Zerubia. In Proc. Urban, Paris, France, April 2007.
Keywords : Road network, Very high resolution, Multiscale, Higher-order, Active contour, Shape.
@INPROCEEDINGS{Peng07_urban,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J.}, |
| title |
= |
{Urban road extraction from VHR images using a multiscale image model and a phase field model of network geometry}, |
| year |
= |
{2007}, |
| month |
= |
{April}, |
| booktitle |
= |
{Proc. Urban}, |
| address |
= |
{Paris, France}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Peng07urban.pdf}, |
| keyword |
= |
{Road network, Very high resolution, Multiscale, Higher-order, Active contour, Shape} |
| } |
Abstract :
This paper addresses the problem of automatically
extracting the main road network in a dense urban area from
a very high resolution optical satellite image using a variational
approach. The model energy has two parts: a phase field higherorder
active contour energy that describes our prior knowledge
of road network geometry, i.e. that it is composed of elongated
structures with roughly parallel borders that meet at junctions;
and a multi-scale statistical image model describing the image
we expect to see given a road network. By minimizing the model
energy, an estimate of the road network is obtained. Promising
results on 0.6m QuickBird Panchromatic images are presented,
and future improvements to the models are outlined. |
|
103 - Image deconvolution using a stochastic differential equation approach.
X. Descombes and M. Lebellego and E. Zhizhina. In Proc. nternational Conference on Computer Vision Theory
and Applications, Barcelona, Spain, March 2007.
Keywords : Deconvolution, Stochastic Differential Equation.
@INPROCEEDINGS{xavBarca2,
|
| author |
= |
{Descombes, X. and Lebellego, M. and Zhizhina, E.}, |
| title |
= |
{Image deconvolution using a stochastic differential equation approach}, |
| year |
= |
{2007}, |
| month |
= |
{March}, |
| booktitle |
= |
{Proc. nternational Conference on Computer Vision Theory
and Applications}, |
| address |
= |
{Barcelona, Spain}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_xavBarca2.pdf}, |
| keyword |
= |
{Deconvolution, Stochastic Differential Equation} |
| } |
|
104 - Circular object segmentation using higher-order active contours.
P. Horvath and I. H. Jermyn and Z. Kato and J. Zerubia. In In Proc. Conference of the Hungarian Association for Image Analysis and Pattern Recognition (KEPAF'07), Debrecen, Hungary, January 2007.
Note : In Hungarian
Keywords : Higher-order, Tree Crown Extraction, Shape.
@INPROCEEDINGS{Horvath07a,
|
| author |
= |
{Horvath, P. and Jermyn, I. H. and Kato, Z. and Zerubia, J.}, |
| title |
= |
{Circular object segmentation using higher-order active contours}, |
| year |
= |
{2007}, |
| month |
= |
{January}, |
| booktitle |
= |
{In Proc. Conference of the Hungarian Association for Image Analysis and Pattern Recognition (KEPAF'07)}, |
| address |
= |
{Debrecen, Hungary}, |
| note |
= |
{In Hungarian}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Horvath07a.pdf}, |
| keyword |
= |
{Higher-order, Tree Crown Extraction, Shape} |
| } |
|
105 - 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} |
| } |
|
106 - 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} |
| } |
|
107 - 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 |
= |
{} |
| } |
|
108 - 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 |
= |
{} |
| } |
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