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Publications of Marie Rochery
Result of the query in the list of publications :
2 Articles |
1 - Higher-Order Active Contour Energies for Gap Closure.
M. Rochery and I. H. Jermyn and J. Zerubia. Journal of Mathematical Imaging and Vision, 29(1): pages 1-20, September 2007.
Keywords : Gap closure, Higher-order, Active contour, Shape, Prior, Road network.
@ARTICLE{Rochery07,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher-Order Active Contour Energies for Gap Closure}, |
| year |
= |
{2007}, |
| month |
= |
{September}, |
| journal |
= |
{Journal of Mathematical Imaging and Vision}, |
| volume |
= |
{29}, |
| number |
= |
{1}, |
| pages |
= |
{1-20}, |
| url |
= |
{http://dx.doi.org/10.1007/s10851-007-0021-x}, |
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{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Rochery07.pdf}, |
| keyword |
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{Gap closure, Higher-order, Active contour, Shape, Prior, Road network} |
| } |
Abstract :
One of the main difficulties in extracting line networks from images, and in particular road networks from remote sensing images, is the existence of interruptions in the data caused, for example, by occlusions. These can lead to gaps in the extracted network that do not correspond to gaps in the real network. In this paper, we describe a higher-order active contour energy that in addition to favouring network-like regions, includes a prior term penalizing networks containing ‘nearby opposing extremities’, thereby making gaps in the extracted network less likely. The new energy term causes such extremities to attract one another during gradient descent. They thus move towards one another and join, closing the gap. To minimize the energy, we develop specific techniques to handle the high-order derivatives that appear in the gradient descent equation. We present the results of automatic extraction of networks from real remote-sensing images, showing the ability of the model to overcome interruptions. |
|
2 - Higher Order Active Contours.
M. Rochery and I. H. Jermyn and J. Zerubia. International Journal of Computer Vision, 69(1): pages 27--42, August 2006.
Keywords : Active contour, Shape, Higher-order, Prior, Road network.
@ARTICLE{mr_ijcv_06,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher Order Active Contours}, |
| year |
= |
{2006}, |
| month |
= |
{August}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{69}, |
| number |
= |
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| pages |
= |
{27--42}, |
| url |
= |
{http://dx.doi.org/10.1007/s11263-006-6851-y}, |
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| keyword |
= |
{Active contour, Shape, Higher-order, Prior, Road network} |
| } |
Abstract :
We introduce a new class of active contour models that
hold great promise for region and shape modelling, and
we apply a special case of these models to the
extraction of road networks from satellite and aerial
imagery. The new models are arbitrary polynomial
functionals on the space of boundaries, and thus
greatly generalize the linear functionals used in
classical contour energies. While classical energies
are expressed as single integrals over the contour,
the new energies incorporate multiple integrals, and
thus describe long-range interactions between
different sets of contour points. As prior terms, they
describe families of contours that share complex
geometric properties, without making reference to any
particular shape, and they require no pose estimation.
As likelihood terms, they can describe multi-point
interactions between the contour and the data. To
optimize the energies, we use a level set approach.
The forces derived from the new energies are non-local
however, thus necessitating an extension of standard
level set methods. Networks are a shape family of
great importance in a number of applications,
including remote sensing imagery. To model them, we
make a particular choice of prior quadratic energy
that describes reticulated structures, and augment it
with a likelihood term that couples the data at pairs
of contour points to their joint geometry. Promising
experimental results are shown on real images. |
|
 top of the page
PhD Thesis and Habilitation |
1 - Contours actifs d'ordre supérieur et leur application à la détection de linéiques dans des images de télédétection.
M. Rochery. PhD Thesis, Universite de Nice Sophia Antipolis, Sophia Antipolis, September 2005.
Keywords : Active contour, Higher-order, Phase Field, Line networks, Road network.
@PHDTHESIS{rochery_these,
|
| author |
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{Rochery, M.}, |
| title |
= |
{Contours actifs d'ordre supérieur et leur application à la détection de linéiques dans des images de télédétection}, |
| year |
= |
{2005}, |
| month |
= |
{September}, |
| school |
= |
{Universite de Nice Sophia Antipolis}, |
| address |
= |
{Sophia Antipolis}, |
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= |
{http://hal.inria.fr/docs/00/04/86/28/PDF/tel-00010631.pdf}, |
| keyword |
= |
{Active contour, Higher-order, Phase Field, Line networks, Road network} |
| } |
|
top of the page
5 Conference articles |
1 - Phase field models and higher-order active contours.
M. Rochery and I. H. Jermyn and J. Zerubia. In Proc. IEEE International Conference on Computer Vision (ICCV), Beijing, China, October 2005.
Keywords : Active contour, Higher-order, Shape, Line networks, Road network, Phase Field.
@INPROCEEDINGS{rochery_iccv05,
|
| author |
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{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Phase field models and higher-order active contours}, |
| year |
= |
{2005}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Computer Vision (ICCV)}, |
| address |
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{Beijing, China}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_iccv05.pdf}, |
| keyword |
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{Active contour, Higher-order, Shape, Line networks, Road network, Phase Field} |
| } |
Abstract :
The representation and modelling of regions is an important topic in computer vision. In this paper, we represent a region via a level set of a `phase field' function. The function is not constrained, eg to be a distance function; nevertheless, phase field energies equivalent to classical active contour energies can be defined. They represent an advantageous alternative to other methods: a linear representation space; ease of implementation (a PDE with no reinitialization); neutral initialization; greater topological freedom. We extend the basic phase field model with terms that reproduce `higher-order active contour' energies, a powerful way of including prior geometric knowledge in the active contour framework via nonlocal interactions between contour points. In addition to the above advantages, the phase field greatly simplifies the analysis and implementation of the higher-order terms. We define a phase field model that favours regions composed of thin arms meeting at junctions, combine this with image terms, and apply the model to the extraction of line networks from remote sensing images. |
|
2 - New Higher-order Active Contour Energies for Network Extraction.
M. Rochery and I. H. Jermyn and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Genoa, Italy, September 2005.
Keywords : Gap closure, Shape, Prior, Higher-order, Active contour.
@INPROCEEDINGS{rochery_icip05,
|
| author |
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{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
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{New Higher-order Active Contour Energies for Network Extraction}, |
| year |
= |
{2005}, |
| month |
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{September}, |
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{Proc. IEEE International Conference on Image Processing (ICIP)}, |
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{Genoa, Italy}, |
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| keyword |
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{Gap closure, Shape, Prior, Higher-order, Active contour} |
| } |
Abstract :
Using the framework of higher-order active contours, we present a new quadratic em continuation energy for the extraction of line networks (e.g. road, hydrographic, vascular) in the presence of occlusions. Occlusions create gaps in the data that frequently translate to gaps in the extracted network. The new energy penalizes earby opposing extremities of the network, and thus favours the closure of the gaps created by occlusions. Nearby opposing extremities are identified using a
sophisticated interaction between pairs of points on the contour. This new model allows the extraction of fully connected networks, even though occlusions violate common assumptions about the homogeneity of the
interior, and high contrast with the exterior, of the network. We present experimental results on real aerial images that demonstrate the effectiveness of the new model for network extraction tasks. |
|
3 - Gap closure in (road) networks using higher-order active contours.
M. Rochery and I. H. Jermyn and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Singapore, October 2004.
Keywords : Active contour, Gap closure, Higher-order, Shape, Road network.
@INPROCEEDINGS{Rochery04,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Gap closure in (road) networks using higher-order active contours}, |
| year |
= |
{2004}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
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{Singapore}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_icip04.pdf}, |
| keyword |
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{Active contour, Gap closure, Higher-order, Shape, Road network} |
| } |
Abstract :
We present a new model for the extraction of networks from images in the presence of occlusions. Such occlusions cause gaps in the extracted network that need to be closed. Using higher-order active contours, which allow the incorporation of sophisticated geometric information, we introduce a new, non-local, `gap closure' force that causes pairs of network extremities that are close together to extend towards one another and join, thus closing the gap
between them. We demonstrate the benefits of the model using the problem of road network extraction, presenting results on aerial images. |
|
4 - Higher Order Active Contours and their Application to the Detection of Line Networks in Satellite Imagery.
M. Rochery and I. H. Jermyn and J. Zerubia. In Proc. IEEE Workshop Variational, Geometric and Level Set Methods in Computer Vision, at ICCV, Nice, France, October 2003.
Keywords : Higher-order, Active contour, Shape, Road network, Segmentation, Prior.
@INPROCEEDINGS{Rochery03a,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher Order Active Contours and their Application to the Detection of Line Networks in Satellite Imagery}, |
| year |
= |
{2003}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE Workshop Variational, Geometric and Level Set Methods in Computer Vision}, |
| address |
= |
{at ICCV, Nice, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_vlsm03.pdf}, |
| keyword |
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{Higher-order, Active contour, Shape, Road network, Segmentation, Prior} |
| } |
Abstract :
We present a novel method for the incorporation of shape information
into active contour models, and apply it to the extraction
of line networks (e.g. road, water) from satellite imagery.
The method is based on a new class of contour energies.
These energies are quadratic on the space of one-chains
in the image, as opposed to classical energies, which are linear.
They can be expressed as double integrals on the contour,
and thus incorporate non-trivial interactions between
different contour points. The new energies describe families
of contours that share complex geometric properties, without
making reference to any particular shape. Networks fall
into such a family, and to model them we make a particular
choice of quadratic energy whose minima are reticulated.
To optimize the energies, we use a level set approach. The
forces derived from the new energies are non-local however,
thus necessitating an extension of standard level set methods.
Promising experimental results are obtained using real
images. |
|
5 - Étude D'une Nouvelle Classe de Contours Actifs Pour la Détection de Routes Dans Des Images de Télédétection.
M. Rochery and I. H. Jermyn and J. Zerubia. In Proc. GRETSI Symposium on Signal and Image Processing, Paris, France, September 2003.
@INPROCEEDINGS{Rochery03,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Étude D'une Nouvelle Classe de Contours Actifs Pour la Détection de Routes Dans Des Images de Télédétection}, |
| year |
= |
{2003}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. GRETSI Symposium on Signal and Image Processing}, |
| address |
= |
{Paris, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_gretsi03.pdf}, |
| keyword |
= |
{} |
| } |
|
top of the page
3 Technical and Research Reports |
1 - Higher-Order Active Contour Energies for Gap Closure.
M. Rochery and I. H. Jermyn and J. Zerubia. Research Report 5717, INRIA, France, October 2005.
Keywords : Road network, Continuity, Gap closure, Higher-order, Active contour, Shape.
@TECHREPORT{RR_5717,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher-Order Active Contour Energies for Gap Closure}, |
| year |
= |
{2005}, |
| month |
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{October}, |
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{5717}, |
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{France}, |
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| keyword |
= |
{Road network, Continuity, Gap closure, Higher-order, Active contour, Shape} |
| } |
Résumé :
L'un des principaux problèmes lors de l'extraction de réseaux
linéiques dans des images, et en particulier l'extraction de réseaux
routiers dans des images de télédétection, est l'existence d'interruptions
dans les données, causées, par exemple, par des occultations. Ces
interruptions peuvent mener à des trous dans le réseau extrait qui
n'existent pas dans le réseau réel. Dans ce rapport, nous décrivons une
énergie de contour actif d'ordre supérieur qui, en plus de favoriser les
régions composées de bras fins et connectés entre eux, inclut un terme d'a
priori qui pénalise les configurations du réseau où des extremités proches
et se faisant face apparaissent. L'apparition dans le réseau extrait de ces
configurations est donc moins probable. Si des extremités proches et se
faisant face apparaissent pendant l'évolution par descente de gradient
utilisée pour minimiser l'énergie, le nouveau terme dans l'énergie crée une
attraction entre ces extremités, qui se rapprochent donc l'une de l'autre
et se rejoignent, fermant ainsi le trou entre elles. Pour minimiser
l'énergie, nous développons des techniques spécifiques pour traiter les
derivées d'ordre élevé qui apparaissent dans l'équation de descente de
gradient. Nous présentons des résultats d'extraction automatique de réseaux
routiers à partir d'images de télédétection, montrant ainsi la capacité du
modèle à surmonter les interruptions. |
Abstract :
One of the main difficulties in extracting line networks from
images, and in particular road networks from remote sensing images, is the
existence of interruptions in the data caused, for example, by occlusions.
These can lead to gaps in the extracted network that do not correspond to
gaps in the real network. In this report, we describe a higher-order active
contour energy that in addition to favouring network-like regions composed
of thin arms joining at junctions, also includes a prior term that
penalizes network configurations containing `nearby opposing extremities',
and thereby makes their appearance in the extracted network less likely. If
nearby opposing extremities form during the gradient descent evolution used
to minimize the energy, the new energy term causes the extremities to
attract one another, and hence to move towards one another and join, thus
closing the gap. To minimize the energy, we develop specific techniques to
handle the high-order derivatives that appear in the gradient descent
equation. We present the results of automatic extraction of networks from
real remote-sensing images, showing the ability of the model to overcome
interruptions. |
|
2 - Higher Order Active Contours.
M. Rochery and I. H. Jermyn and J. Zerubia. Research Report 5656, INRIA, France, August 2005.
Keywords : Active contour, Higher-order, Road network, Shape, Prior.
@TECHREPORT{RR_5656,
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Résumé :
Nous introduisons une nouvelle classe de contours actifs qui offre des perspectives intéressantes pour la modélisation des régions et des formes, et nous appliquons un cas particulier de ces modèles à l'extraction de réseaux linéiques dans des images satellitaires et aériennes. Les nouveaux modèles sont des fonctionnelles polynômiales arbitraires sur l'espace des contours, et généralisent ainsi les fonctionnelles linéaires utilisées dans les modèles classiques de contours actifs. Alors que les fonctionnelles classiques s'écrivent avec de simples intégrales sur le contour, les nouvelles énergies sont définies comme des intégrales multiples, décrivant ainsi des interactions de longue portée entre les différents ensembles de points du contour. Utilisées comme des termes d'a priori, les fonctionnelles décrivent des familles de contours aux propriétés géométriques complexes, sans faire référence à une forme spécifique et sans nécessiter l'estimation de la position. Utilisées comme des termes d'attache aux données, elles permettent de décrire des interactions multi-points entre le contour et les données. Afin de minimiser ces énergies, nous adoptons la méthodologie des courbes de niveau. Les forces dérivées des énergies sont cependant non locales, et nécessitent une extension des méthodes de courbes de niveau standard. Les réseaux sont une famille de formes d'une grande importance dans de nombreuses applications et en particulier en télédétection. Pour les modéliser, nous faisons un choix particulier d'énergie quadratique qui décrit des structures branchées et nous ajoutons un terme d'attache aux données qui lie les données et la géométrie du contour au niveau des paires de points du contour. Des résultats d'extraction prometteurs sont montrés sur des images réelles. |
Abstract :
We introduce a new class of active contour models that hold great promise for region and shape modelling, and we apply a special case of these models to the extraction of road networks from satellite and aerial imagery. The new models are arbitrary polynomial functionals on the space of boundaries, and thus greatly generalize the linear functionals used in classical contour energies. While classical energies are expressed as single integrals over the contour, the new energies incorporate multiple integrals, and thus describe long-range interactions between different sets of contour points. As prior terms, they describe families of contours that share complex geometric properties, without making reference to any particular shape, and they require no pose estimation. As likelihood terms, they can describe multi-point interactions between the contour and the data. To optimize the energies, we use a level set approach. The forces derived from the new energies are non-local however, thus necessitating an extension of standard level set methods. Networks are a shape family of great importance in a number of applications, including remote sensing imagery. To model them, we make a particular choice of prior quadratic energy that describes reticulated structures, and augment it with a likelihood term that couples the data at pairs of contour points to their joint geometry. Promising experimental results are shown on real images. |
|
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