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Publications sur Change detection
Résultat de la recherche dans la liste des publications :
4 Articles |
1 - Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics.
C. Benedek et X. Descombes et J. Zerubia. IEEE Trans. Pattern Analysis and Machine Intelligence, 34(1): pages 33-50, janvier 2012.
Mots-clés : Building extraction, Change detection, Processus ponctuels marques, multiple birth-and-death dynamics.
Copyright : IEEE
@ARTICLE{benedekPAMI11,
|
| author |
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{Benedek, C. and Descombes, X. and Zerubia, J.}, |
| title |
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{Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics}, |
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{2012}, |
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{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
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{33-50}, |
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{http://dx.doi.org/10.1109/TPAMI.2011.94}, |
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{Building extraction, Change detection, Processus ponctuels marques, multiple birth-and-death dynamics} |
| } |
Abstract :
In this paper we introduce a new probabilistic method which integrates building extraction with change detection in remotely sensed image pairs. A global optimization process attempts to find the optimal configuration of buildings, considering the observed data, prior knowledge, and interactions between the neighboring building parts. We present methodological contributions in three key issues: (1) We implement a novel object-change modeling approach based on Multitemporal Marked Point Processes, which simultaneously exploits low level change information between the time layers and object level building description to recognize and separate changed and unaltered buildings. (2) To answering the challenges of data heterogeneity in aerial and satellite image repositories, we construct a flexible hierarchical framework which can create various building appearance models from different elementary feature based modules. (3) To simultaneously ensure the convergence, optimality and computation complexity constraints raised by the increased data quantity, we adopt the quick Multiple Birth and Death optimization technique for change detection purposes, and propose a novel non-uniform stochastic object birth process, which generates relevant objects with higher probability based on low-level image features. |
|
2 - On the Illumination Invariance of the Level Lines under Directed Light: Application to Change Detection.
P. Weiss et A. Fournier et L. Blanc-Féraud et G. Aubert. SIAM Journal on Imaging Sciences, 4(1): pages 448-471, mars 2011.
Mots-clés : Level Lines, topographic map, illumination invariance, Change detection, contrast equalization, remote sensing.
@ARTICLE{SIIMS_2011,
|
| author |
= |
{Weiss, P. and Fournier, A. and Blanc-Féraud, L. and Aubert, G.}, |
| title |
= |
{On the Illumination Invariance of the Level Lines under Directed Light: Application to Change Detection}, |
| year |
= |
{2011}, |
| month |
= |
{mars}, |
| journal |
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{SIAM Journal on Imaging Sciences}, |
| volume |
= |
{4}, |
| number |
= |
{1}, |
| pages |
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{448-471}, |
| url |
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{http://www.math.univ-toulouse.fr/~weiss/Publis/SIIMS_2011_Weiss.pdf}, |
| pdf |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/SIIMS_2011_Weiss.pdf}, |
| keyword |
= |
{Level Lines, topographic map, illumination invariance, Change detection, contrast equalization, remote sensing} |
| } |
Abstract :
We analyze the illumination invariance of the level lines of an image. We show that if the scene
surface has Lambertian reflectance and the light is directed, then a necessary and sufficient condition
for the level lines to be illumination invariant is that the three-dimensional scene be developable and
that its albedo satisfy some geometrical constraints. We then show that the level lines are “almost”
invariant for piecewise developable surfaces. Such surfaces fit most of the urban structures. This
allows us to devise a fast and simple algorithm that detects changes between pairs of remotely
sensed images of urban areas, independently of the lighting conditions. We show the effectiveness of
the algorithm both on synthetic OpenGL scenes and real QuickBird images. The synthetic results
illustrate the theory developed in this paper. The two real QuickBird images show that the proposed
change detection algorithm is discriminant. For easy scenes it achieves a rate of 85% detected changes
for 10% false positives, while it reaches a rate of 75% detected changes for 25% false positives on
demanding scenes.
|
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3 - Detection of Object Motion Regions in Aerial Image Pairs with a Multi-Layer Markovian Model.
C. Benedek et T. Szirányi et Z. Kato et J. Zerubia. IEEE Trans. Image Processing, 18(10): pages 2303-2315, octobre 2009.
Mots-clés : Change detection, Aerial images, Camera motion, MRF.
@ARTICLE{benedekTIP09,
|
| author |
= |
{Benedek, C. and Szirányi, T. and Kato, Z. and Zerubia, J.}, |
| title |
= |
{Detection of Object Motion Regions in Aerial Image Pairs with a Multi-Layer Markovian Model}, |
| year |
= |
{2009}, |
| month |
= |
{octobre}, |
| journal |
= |
{IEEE Trans. Image Processing}, |
| volume |
= |
{18}, |
| number |
= |
{10}, |
| pages |
= |
{2303-2315}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5089480}, |
| keyword |
= |
{Change detection, Aerial images, Camera motion, MRF} |
| } |
Abstract :
We propose a new Bayesian method for detecting the regions of object displacements in aerial image pairs. We use a robust but coarse 2-D image registration algorithm. Our main challenge is to eliminate the registration errors from the extracted change map. We introduce a three-layer Markov Random Field model which integrates information from two different features, and ensures connected homogeneous regions in the segmented images. Validation is given on real aerial photos. |
|
4 - Change Detection in Optical Aerial Images by a Multi-Layer Conditional Mixed Markov Model.
C. Benedek et T. Szirányi. IEEE Trans. Geoscience and Remote Sensing, 47(10): pages 3416-3430, octobre 2009.
Mots-clés : mixed Markov models, Change detection, Aerial images, Estimation MAP.
Copyright : IEEE
@ARTICLE{benedekTGRS09,
|
| author |
= |
{Benedek, C. and Szirányi, T.}, |
| title |
= |
{Change Detection in Optical Aerial Images by a Multi-Layer Conditional Mixed Markov Model}, |
| year |
= |
{2009}, |
| month |
= |
{octobre}, |
| journal |
= |
{IEEE Trans. Geoscience and Remote Sensing}, |
| volume |
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{47}, |
| number |
= |
{10}, |
| pages |
= |
{3416-3430}, |
| url |
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| keyword |
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{mixed Markov models, Change detection, Aerial images, Estimation MAP} |
| } |
Abstract :
In this paper we propose a probabilistic model for detecting relevant changes in registered aerial image pairs taken with the time differences of several years and in different seasonal conditions. The introduced approach, called the Conditional Mixed Markov model (CXM), is a combination of a mixed Markov model and a conditionally independent random field of signals. The model integrates global intensity statistics with local correlation and contrast features. A global energy optimization process ensures simultaneously optimal local feature selection and smooth, observation-consistent segmentation. Validation is given on real aerial image sets provided by the Hungarian Institute of Geodesy, Cartography and Remote Sensing and Google Earth. |
|
 haut de la page
Thèse de Doctorat et Habilitation |
1 - Algorithmes rapides d'optimisation convexe. Application à la reconstruction d'images et à la détection de changements.
P. Weiss. Thèse de Doctorat, Universite de Nice Sophia Antipolis, novembre 2008.
Mots-clés : Convex optimization, nesterov scheme, Sparse representations, Variation totale, Change detection, level lines.
Copyright :
@PHDTHESIS{These_Pweiss,
|
| author |
= |
{Weiss, P.}, |
| title |
= |
{Algorithmes rapides d'optimisation convexe. Application à la reconstruction d'images et à la détection de changements}, |
| year |
= |
{2008}, |
| month |
= |
{novembre}, |
| school |
= |
{Universite de Nice Sophia Antipolis}, |
| pdf |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/These_PWEISS_Compressee.pdf}, |
| keyword |
= |
{Convex optimization, nesterov scheme, Sparse representations, Variation totale, Change detection, level lines} |
| } |
Résumé :
Cette thèse contient des contributions en analyse numérique et en vision par ordinateur. Dans une première partie, nous nous intéressons à la résolution rapide, par des méthodes de premier ordre, de problèmes d'optimisation convexe. Ces problèmes apparaissent naturellement dans de nombreuses tâches telles que la reconstruction d'images, l'échantillonnage compressif ou la décomposition d'images en texture et en géométrie. Ils ont la particularité d'être non différentiables ou très mal conditionnés. On montre qu'en utilisant des propriétés fines des fonctions à minimiser on peut obtenir des algorithmes de minimisation extrêmement efficaces. On analyse systématiquement leurs taux de convergence en utilisant des résultats récents dûs à Y. Nesterov. Les méthodes proposées correspondent - à notre connaissance - à l'état de l'art des méthodes de premier ordre. Dans une deuxième partie, nous nous intéressons au problème de la détection de changements entre deux images satellitaires prises au même endroit à des instants différents. Une des difficultés principales à surmonter pour résoudre ce problème est de s'affranchir des conditions d'illuminations différentes entre les deux prises de vue. Ceci nous mène à l'étude de l'invariance aux changements d'illuminations des lignes de niveau d'une image. On caractérise complètement les scènes qui fournissent des lignes de niveau invariantes. Celles-ci correspondent assez bien à des milieux urbains. On propose alors un algorithme simple de détection de changements qui fournit des résultats très satisfaisants sur des images synthétiques et des images Quickbird réelles. |
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7 Articles de conférence |
1 - Building Extraction and Change Detection in Multitemporal Remotely Sensed Images with Multiple Birth and Death Dynamics.
C. Benedek et X. Descombes et J. Zerubia. Dans IEEE Workshop on Applications of Computer Vision (WACV), pages 100-105, Snowbird, Utah, USA, décembre 2009.
Mots-clés : Processus ponctuels marques, Change detection, Aerial images, Building extraction, Imagerie satellitaire.
@INPROCEEDINGS{benedekWacv09,
|
| author |
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{2009}, |
| month |
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{Processus ponctuels marques, Change detection, Aerial images, Building extraction, Imagerie satellitaire} |
| } |
Abstract :
In this paper we introduce a new probabilistic method which integrates building extraction with change detection in remotely sensed image pairs. A global optimization process attempts to find the optimal configuration of buildings, considering the observed data, prior knowledge, and interactions between the neighboring building parts. The accuracy is ensured by a Bayesian object model verification, meanwhile the computational cost is significantly decreased by a non-uniform stochastic object birth process, which proposes relevant objects with higher probability based on low-level image features.
|
|
2 - Conditional mixed-state model for structural change analysis from very high resolution optical images.
B. Belmudez et V. Prinet et J.F. Yao et P. Bouthemy et X. Descombes. Dans Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, juillet 2009.
Mots-clés : Change detection, mixed Markov models.
@INPROCEEDINGS{bel09,
|
| author |
= |
{Belmudez, B. and Prinet, V. and Yao, J.F. and Bouthemy, P. and Descombes, X.}, |
| title |
= |
{Conditional mixed-state model for structural change analysis from very high resolution optical images}, |
| year |
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{2009}, |
| month |
= |
{juillet}, |
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{IGARSS}, |
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{Cape Town, South Africa}, |
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= |
{http://hal.archives-ouvertes.fr/inria-00398062/}, |
| keyword |
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{Change detection, mixed Markov models} |
| } |
Abstract :
The present work concerns the analysis of dynamic scenes from earth observation images. We are interested in building a map which, on one hand locates places of change, on the other hand, reconstructs a unique visual information of the non-change areas. We show in this paper that such a problem can naturally be takled with conditional mixed-state random field modeling (mixed-state CRF), where the ”mixed state” refers to the symbolic or continous nature of the unknown variable. The maximum a posteriori (MAP) estimation of the CRF is, through the Hammersley-Clifford theorem, turned into an energy minimisation problem. We tested the model on several Quickbird images and illustrate the quality of the results. |
|
3 - A Mixed Markov Model for Change Detection in Aerial Photos with Large Time Differences.
C. Benedek et T. Szirányi. Dans Proc. International Conference on Pattern Recognition (ICPR), Tampa, USA, décembre 2008.
Mots-clés : Aerial images, Change detection, mixed Markov models.
@INPROCEEDINGS{benedekICPR08,
|
| author |
= |
{Benedek, C. and Szirányi, T.}, |
| title |
= |
{A Mixed Markov Model for Change Detection in Aerial Photos with Large Time Differences}, |
| year |
= |
{2008}, |
| month |
= |
{décembre}, |
| booktitle |
= |
{Proc. International Conference on Pattern Recognition (ICPR)}, |
| address |
= |
{Tampa, USA}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/35/91/16/PDF/benedekICPR08.pdf}, |
| keyword |
= |
{Aerial images, Change detection, mixed Markov models} |
| } |
Abstract :
In the paper we propose a novel multi-layer Mixed Markov model for detecting relevant changes in registered aerial images taken with significant time differences. The introduced approach combines global intensity statistics with local correlation and contrast features. A global energy optimization process simultaneously ensures optimal local feature selection and smooth, observation-consistent classification. Validation is given on real aerial photos. |
|
4 - A contrast equalization procedure for change detection algorithms: applications to remotely sensed images of urban areas.
A. Fournier et P. Weiss et L. Blanc-Féraud et G. Aubert. Dans International Conference on Pattern Recognition (ICPR), Tampa, USA, décembre 2008.
Mots-clés : Change detection, Level Lines, remote sensing.
Copyright : ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
@INPROCEEDINGS{l_lines_icpr08,
|
| author |
= |
{Fournier, A. and Weiss, P. and Blanc-Féraud, L. and Aubert, G.}, |
| title |
= |
{A contrast equalization procedure for change detection algorithms: applications to remotely sensed images of urban areas}, |
| year |
= |
{2008}, |
| month |
= |
{décembre}, |
| booktitle |
= |
{International Conference on Pattern Recognition (ICPR)}, |
| address |
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{Tampa, USA}, |
| url |
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{http://www.math.univ-toulouse.fr/~weiss/Publis/Conferences/icpr2008.pdf}, |
| pdf |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/Conferences/icpr2008.pdf}, |
| keyword |
= |
{Change detection, Level Lines, remote sensing} |
| } |
|
5 - Mixing Geometric and Radiometric Features for Change Classification.
A. Fournier et X. Descombes et J. Zerubia. Dans Proc. SPIE Symposium on Electronic Imaging, San Jose, USA, janvier 2008.
Mots-clés : 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 |
= |
{janvier}, |
| 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. |
|
6 - A Multi-Layer MRF Model for Object-Motion Detection in Unregistered Airborne Image-Pairs.
C. Benedek et T. Szirányi et Z. Kato et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Vol. 6, pages 141--144, San Antonio, Texas, USA, septembre 2007.
Mots-clés : Change detection, Aerial images, Camera motion, MRF.
Copyright : Copyright IEEE
@INPROCEEDINGS{benedek_ICIP07,
|
| author |
= |
{Benedek, C. and Szirányi, T. and Kato, Z. and Zerubia, J.}, |
| title |
= |
{A Multi-Layer MRF Model for Object-Motion Detection in Unregistered Airborne Image-Pairs}, |
| year |
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{2007}, |
| month |
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{septembre}, |
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{Proc. IEEE International Conference on Image Processing (ICIP)}, |
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| pages |
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{141--144}, |
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{San Antonio, Texas, USA}, |
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{http://web.eee.sztaki.hu/~bcsaba/Publications/Pdf/benedek_icip2007.pdf}, |
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{Change detection, Aerial images, Camera motion, MRF} |
| } |
Abstract :
In this paper, we give a probabilistic model for automatic change detection on airborne images taken with moving cameras. To ensure robustness, we adopt an unsupervised coarse matching instead of a precise image registration. The challenge of the proposed model is to eliminate the registration errors, noise and the parallax artifacts caused by the static objects having considerable height (buildings, trees, walls etc.) from the difference image. We describe the background membership of a given image point through two different features, and introduce a novel three-layerMarkov Random Field (MRF) model to ensure connected homogenous regions in the segmented image. |
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7 - Vers une détection et une classification non-supervisées des changements inter-images.
A. Fournier et X. Descombes et J. Zerubia. Dans Proc. Traitement et Analyse de l'Information - Méthodes et Applications (TAIMA), 2007.
Mots-clés : Markov Random Fields, Registration, Change detection, Clustering.
@INPROCEEDINGS{fournier-taima-07,
|
| author |
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{Fournier, A. and Descombes, X. and Zerubia, J.}, |
| title |
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{Vers une détection et une classification non-supervisées des changements inter-images}, |
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{2007}, |
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{Proc. Traitement et Analyse de l'Information - Méthodes et Applications (TAIMA)}, |
| pdf |
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| keyword |
= |
{Markov Random Fields, Registration, Change detection, Clustering} |
| } |
|
haut de la page
3 Rapports de recherche et Rapports techniques |
1 - Building Extraction and Change Detection in Multitemporal Aerial and Satellite Images in a Joint Stochastic Approach.
C. Benedek et X. Descombes et J. Zerubia. Rapport de Recherche 7143, INRIA, Sophia Antipolis, décembre 2009.
Mots-clés : Change detection, Building extraction, Processus ponctuels marques, MAP, multiple birth-and-death dynamics.
@TECHREPORT{benedekRR_09,
|
| author |
= |
{Benedek, C. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Building Extraction and Change Detection in Multitemporal Aerial and Satellite Images in a Joint Stochastic Approach}, |
| year |
= |
{2009}, |
| month |
= |
{décembre}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{7143}, |
| address |
= |
{Sophia Antipolis}, |
| url |
= |
{http://hal.archives-ouvertes.fr/inria-00426615}, |
| keyword |
= |
{Change detection, Building extraction, Processus ponctuels marques, MAP, multiple birth-and-death dynamics} |
| } |
Résumé :
Dans ce rapport, nous proposons une nouvelle méthode probabiliste qui intègre l'extraction de bâtiments et la détection de changements à partir de paires d'images de télédétection. Un algorithme d'optimisation globale permet de trouver la configuration optimale de bâtiments en considérant des observations, des connaissances a priori et des interactions entre des parties voisines de bâtiments. La précision est assurée par une vérification d'un modèle objet bayésien; le coût du calcul est considérablement réduit en utilisant un processus stochastique non-uniforme de naissance d'objets fondé sur des caractéristiques bas-niveaux des images, qui génère des objets pertinents ayant une grande probabilité. |
Abstract :
In this report we introduce a new probabilistic method which integrates building extraction with change detection in remotely sensed image pairs. A global optimization process attempts to find the optimal configuration of buildings, considering the observed data, prior knowledge, and interactions between the neighboring building parts. The accuracy is ensured by a Bayesian object model verification, meanwhile the computational cost is significantly decreased by a non-uniform stochastic object birth process, which proposes relevant objects with higher probability based on low-level image features. |
|
2 - On the illumination invariance of the level lines under directed light. Application to change detection.
P. Weiss et A. Fournier et L. Blanc-Féraud et G. Aubert. Rapport de Recherche 6612, INRIA, 2008.
Mots-clés : Level Lines, illumination invariance, topographic map, Change detection, remote sensing, Zones urbaines.
Copyright :
@TECHREPORT{RR-6612,
|
| author |
= |
{Weiss, P. and Fournier, A. and Blanc-Féraud, L. and Aubert, G.}, |
| title |
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{On the illumination invariance of the level lines under directed light. Application to change detection}, |
| year |
= |
{2008}, |
| institution |
= |
{INRIA}, |
| type |
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{Research Report}, |
| number |
= |
{6612}, |
| url |
= |
{https://hal.archives-ouvertes.fr/inria-00310383}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/31/03/83/PDF/RR-6612.pdf}, |
| keyword |
= |
{Level Lines, illumination invariance, topographic map, Change detection, remote sensing, Zones urbaines} |
| } |
Abstract :
We analyze the illumination invariance of the level lines of an image. We show that if the scene surface has Lambertian reflectance and the light is directed, then a necessary condition for the level lines to be illumination invariant is that the 3D scene be developable and that its albedo satisfies some geometrical constraints. We then show that the level lines are ``almost'' invariant for piecewise developable surfaces. Such surfaces fit most of the urban structures. In a second part, this allows us to devise a very fast algorithm that detects changes between pairs of remotely sensed images of urban areas, independently of the lighting conditions. We show the effectiveness of the algorithm both on synthetic OpenGL scenes and real Quickbird images. We compare the efficiency of the proposed algorithm with other classical approaches and show that it is superior both in practice and in theory. |
|
3 - A Three-layer MRF model for Object Motion Detection in Airborne Images.
C. Benedek et T. Szirányi et Z. Kato et J. Zerubia. Rapport de Recherche 6208, INRIA, juin 2007.
Mots-clés : Aerial images, Change detection, Camera motion, MRF.
@TECHREPORT{benedek_INRIARR07,
|
| author |
= |
{Benedek, C. and Szirányi, T. and Kato, Z. and Zerubia, J.}, |
| title |
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{A Three-layer MRF model for Object Motion Detection in Airborne Images}, |
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{2007}, |
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{https://hal.inria.fr/inria-00150805}, |
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= |
{https://hal.inria.fr/inria-00150805}, |
| keyword |
= |
{Aerial images, Change detection, Camera motion, MRF} |
| } |
|
haut de la page
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Rapport d'activité 2011
bibtex
