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498 results on '"Zerubia, Josiane"'

4. A Two-Stage Road Segmentation Approach for Remote Sensing Images

Author

Li, Tianyu, Comer, Mary, Zerubia, Josiane, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Rousseau, Jean-Jacques, editor, and Kapralos, Bill, editor

Published
2023
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6. Progressive Tree-like Curvilinear Structure Reconstruction with Structured Ranking Learning and Graph Algorithm

Author

Jeong, Seong-Gyun, Tarabalka, Yuliya, Nisse, Nicolas, and Zerubia, Josiane

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We propose a novel tree-like curvilinear structure reconstruction algorithm based on supervised learning and graph theory. In this work we analyze image patches to obtain the local major orientations and the rankings that correspond to the curvilinear structure. To extract local curvilinear features, we compute oriented gradient information using steerable filters. We then employ Structured Support Vector Machine for ordinal regression of the input image patches, where the ordering is determined by shape similarity to latent curvilinear structure. Finally, we progressively reconstruct the curvilinear structure by looking for geodesic paths connecting remote vertices in the graph built on the structured output rankings. Experimental results show that the proposed algorithm faithfully provides topological features of the curvilinear structures using minimal pixels for various datasets.

Published
2016

10. A higher-order active contour model of a `gas of circles' and its application to tree crown extraction

Author

Horvath, Peter, Jermyn, Ian, Kato, Zoltan, and Zerubia, Josiane

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Many image processing problems involve identifying the region in the image domain occupied by a given entity in the scene. Automatic solution of these problems requires models that incorporate significant prior knowledge about the shape of the region. Many methods for including such knowledge run into difficulties when the topology of the region is unknown a priori, for example when the entity is composed of an unknown number of similar objects. Higher-order active contours (HOACs) represent one method for the modelling of non-trivial prior knowledge about shape without necessarily constraining region topology, via the inclusion of non-local interactions between region boundary points in the energy defining the model. The case of an unknown number of circular objects arises in a number of domains, e.g. medical, biological, nanotechnological, and remote sensing imagery. Regions composed of an a priori unknown number of circles may be referred to as a `gas of circles'. In this report, we present a HOAC model of a `gas of circles'. In order to guarantee stable circles, we conduct a stability analysis via a functional Taylor expansion of the HOAC energy around a circular shape. This analysis fixes one of the model parameters in terms of the others and constrains the rest. In conjunction with a suitable likelihood energy, we apply the model to the extraction of tree crowns from aerial imagery, and show that the new model outperforms other techniques.

Published
2006

11. Classification of multimission SAR images based on Probabilistic Graphical Models and Convolutional Neural Networks

Author

Pastorino, Martina, Moser, Gabriele, Serpico, Sebastiano, Zerubia, Josiane, Dipartimento di Ingegneria Navale, Elettrica, Elettronica e delle Telecomunicazioni / Dept. of Electrical, Electronic, Telecommunications Engineering and Naval Architecture (DITEN), Università degli studi di Genova = University of Genoa (UniGe), Télédetection et IA embarqués pour le 'New Space' (AYANA), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and Université Côte d'Azur (UCA)

Subjects
multisensor, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], PGM, FCN, MRF, multimodal SAR imagery, semantic segmentation, CNN
Abstract

International audience; The problem of the semantic segmentation of multimodal images is characterized by the challenge of jointly exploiting information deriving from images possibly acquired at different spatial resolutions, frequencies, and bands. This paper proposes to address this task in the case of multimission synthetic aperture radar (SAR) images, through a combination of fully convolutional networks (FCNs), hierarchical probabilistic graphical models (PGMs), and decision tree ensembles. The objective is to model the spatial and multiresolution information contained in multimodal remote sensing images collected by distinct space missions with SAR payloads. The experimental validation is conducted with COSMO-SkyMed and SAOCOM images over Northern Italy. The results show that the proposed methodology is capable to reach accurate classification maps from input multimission SAR imagery.

Published
2023

13. Marked Point Process Model for Curvilinear Structures Extraction

Author

Jeong, Seong-Gyun, Tarabalka, Yuliya, Zerubia, Josiane, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Tai, Xue-Cheng, editor, Bae, Egil, editor, Chan, Tony F., editor, and Lysaker, Marius, editor

Published
2015
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22. Unsupervised Classification of SAR Images Using Hierarchical Agglomeration and EM

Author

Kayabol, Koray, Krylov, Vladimir A., Zerubia, Josiane, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Salerno, Emanuele, editor, Çetin, A. Enis, editor, and Salvetti, Ovidio, editor

Published
2012
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23. A Theoretical and Numerical Study of a Phase Field Higher-Order Active Contour Model of Directed Networks

Author

El Ghoul, Aymen, Jermyn, Ian H., Zerubia, Josiane, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Kimmel, Ron, editor, Klette, Reinhard, editor, and Sugimoto, Akihiro, editor

Published
2011
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24. Adaptive Birth for the GLMB Filter for Object Tracking in Satellite Videos

Author

Aguilar, Camilo, Ortner, Mathias, Zerubia, Josiane, Télédetection et IA embarqués pour le 'New Space' (AYANA), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Côte d'Azur (UCA), AIRBUS DS (Toulouse), and ANR-15-IDEX-0001,UCA JEDI,Idex UCA JEDI(2015)

Subjects
GLMB, remote sensing, RFS, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], multitarget tracking, adaptive birth
Abstract

International audience; The Generalized Labeled Multi-Bernoulli (GLMB) filter attains remarkable results in Multi-Object Tracking (MOT). Nevertheless, the GLMB filter relies on strong assumptions such as prior knowledge of targets' initial state. Pragmatic scenarios such as satellite video object tracking challenge these assumptions as objects appear at random locations and object detectors output numerous false positives. We present an enhanced version of the GLMB filter that learns from previous trajectories to estimate accurate hypotheses initializations. We keep track of previous target states and use this information to sample the initial velocities of newborn targets. This addition significantly improves the performance of the GLMB in videos with low Frames Per Second (FPS), where the target's initial states are paramount for object tracking. We test this enhanced GLMB filter versus comparable trackers and previous solutions for the GLMB filter and show that our filter obtains better performance. Code is available at https://github.com/Ayana-Inria/GLMB-adaptivebirth-satellite-videos

Published
2022

25. A Two-Stage Road Segmentation Approach for Remote Sensing Images

Author

Li, Tianyu, Comer, Mary, Zerubia, Josiane, Purdue University [West Lafayette], Télédetection et IA embarqués pour le 'New Space' (AYANA), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Côte d'Azur (UCA), and IAPR

Subjects
Road segmentation, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Convolutional neural network (CNN), Two stage learning, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Remote sensing
Abstract

International audience; Many road segmentation methods based on CNNs have been proposed for remote sensing images in recent years. Although these techniques show great performance in various applications, there are still problems in road segmentation, due to the existence of complex backgrounds, illumination changes, and occlusions due to trees and cars. In this paper, we propose a two-stage strategy for road segmentation. A probability map is generated in the first stage by a selected network (ResUnet is used as a case study in this paper), then we attach the probability map image to the original RGB images and feed the resulting four images to a U-Net-like network in the second stage to get a refined result. Our experiments on the Massachusetts road dataset show the average IoU can increase up to 3% from stage one to stage two, which achieves state-of-the-art results on this dataset. Moreover, from the qualitative results, obvious improvements from stage one to stage two can be seen: fewer false positives and better connection of road lines.

Published
2022

27. Parameter Estimation for Marked Point Processes. Application to Object Extraction from Remote Sensing Images

Author

Chatelain, Florent, Descombes, Xavier, Zerubia, Josiane, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Cremers, Daniel, editor, Boykov, Yuri, editor, Blake, Andrew, editor, and Schmidt, Frank R., editor

Published
2009
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28. An Extended Phase Field Higher-Order Active Contour Model for Networks and Its Application to Road Network Extraction from VHR Satellite Images

Author

Peng, Ting, Jermyn, Ian H., Prinet, Véronique, Zerubia, Josiane, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Forsyth, David, editor, Torr, Philip, editor, and Zisserman, Andrew, editor

Published
2008
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29. A Hierarchical Texture Model for Unsupervised Segmentation of Remotely Sensed Images

Author

Scarpa, Giuseppe, Haindl, Michal, Zerubia, Josiane, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Rangan, C. Pandu, editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ersbøll, Bjarne Kjær, editor, and Pedersen, Kim Steenstrup, editor

Published
2007
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30. An Improved ‘Gas of Circles’ Higher-Order Active Contour Model and Its Application to Tree Crown Extraction

Author

Horváth, Péter, Jermyn, Ian H., Kato, Zoltan, Zerubia, Josiane, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kalra, Prem K., editor, and Peleg, Shmuel, editor

Published
2006
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32. Adaptive Simulated Annealing for Energy Minimization Problem in a Marked Point Process Application

Author

Perrin, Guillaume, Descombes, Xavier, Zerubia, Josiane, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Rangarajan, Anand, editor, Vemuri, Baba, editor, and Yuille, Alan L., editor

Published
2005
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36. A Level Set Model for Image Classification

Author

Samson, Christophe, Blanc-Féraud, Laure, Zerubia, Josiane, Aubert, Gilles, Goos, Gerhard, editor, Hartmanis, Juris, editor, van Leeuwen, Jan, editor, Nielsen, Mads, editor, Johansen, Peter, editor, Olsen, Ole Fogh, editor, and Weickert, Joachim, editor

Published
1999
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46. Blind deconvolution for thin-layered confocal imaging

Author

Pankajakshan, Praveen, Zhang, Bo, Blanc-Feraud, Laure, Kam, Zvi, Olivo-Marin, Jean-Christophe, and Zerubia, Josiane

Subjects
Confocal laser scanning microscopy -- Models, Astronomy, Physics
Abstract

We propose an alternate minimization algorithm for estimating the point-spread function (PSF) of a confocal laser scanning microscope and the specimen fluorescence distribution. A three-dimensional separable Gaussian model is used to restrict the PSF solution space and a constraint on the specimen is used so as to favor the stabilization and convergence of the algorithm. The results obtained from the simulation show that the PSF can be estimated to a high degree of accuracy, and those on real data show better deconvolution as compared to a full theoretical PSF model. OCIS codes: 100.1455, 180.1790, 100.3190.

Published
2009

48. A marked point process of rectangles and segments for automatic analysis of digital elevation models

Author

Ortner, Mathias, Descombes, Xavier, and Zerubia, Josiane

Subjects
Algorithm, Technology application, Algorithms -- Methods, Image processing -- Technology application, Poisson processes -- Evaluation, Simulated annealing (Mathematics) -- Evaluation
Abstract

This work presents a framework for automatic feature extraction from images using stochastic geometry. Features in images are modeled as realizations of a spatial point process of geometrical shapes. This framework allows the incorporation of a priori knowledge on the spatial repartition of features. More specifically, we present a model based on the superposition of a process of segments and a process of rectangles. The former is dedicated to the detection of linear networks of discontinuities, whereas the latter aims at segmenting homogeneous areas. An energy is defined, favoring connections of segments, alignments of rectangles, and a relevant interaction between both types of objects. The estimation is performed by minimizing the energy using a simulated annealing algorithm. The proposed model is applied to the analysis of Digital Elevation Models (DEMs). These images are raster data representing the altimetry of a dense urban area. We present results on real data provided by the French National Geographic Institute (IGN) consisting in low-quality DEMs of various types. Index Terms--Image processing, Poisson point process, stochastic geometry, dense urban area, Digital Elevation Models, land register, building detection, MCMC, RJMCMC, simulated annealing.

Published
2008

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