CERTIS

CENTRE D'ENSEIGNEMENT ET DE RECHERCHE EN TECHNOLOGIES DE L’INFORMATION ET SYSTEMES

ACTIVITY REPORT 2005

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CENTRE D'ENSEIGNEMENT ET DE RECHERCHE EN TECHNOLOGIES DE L’INFORMATION ET SYSTEMES

CERTIS

ENPC Laboratory (hosting joint projects with INRIA, ENS, CNRS and UNSA)

Ecole Nationale des Ponts et Chaussées

6-8 av. Blaise Pascal - Cité Descartes - 77455 Marne-la-Vallée Cedex 2 Web: http://www.enpc.fr/certis

Tel.: (33) 1 64 15 21 72 - Fax: (33) 1 64 15 22 99

Director: Renaud Keriven Project leaders: Olivier Faugeras Nikos Paragios/Florent Ségonne Jean-Pierre.Merlet

18 research scientists (6 ENPC) 31 PhD students (12 ENPC) 1 technical staff 9 visiting scientists 4 administrative assistants (2 ENPC) 9 graduate students interns (5 ENPC) 4 post-doctoral fellows (1 ENPC) 11 student interns (7 ENPC) The CERTIS (Centre d'Enseignement et de Recherche en Technologies de l'Information et Systèmes) is the Center for Education and Research in Computer Science of the Ecole Nationale des Ponts et Chaussées. The CERTIS hosts three research projects:

• The ENPC/INRIA/ENS Odyssée pro-ject (leader: O. Faugeras), working on algorithmic and biological vision, cerebral imaging, and brain activity modeling.

• The ENPC VisAGe project (leaders: N. Paragios/ F. Ségonne), that focuses

on computer vision, learning theory and discrete geometry for virtual reality and medical imaging.

• The ENPC/INRIA/UNSA/CNRS Coprin project (leader: J.P. Merlet), working on constraint programming.

As a Center for Education and Research, the CERTIS is also deeply involved in the ENPC educational programs as well as in other graduating courses.

I. RESEARCH I.1. ODYSSEE Project Joint Project between ENPC, INRIA & ENS - Leader: O.Faugeras The Odyssée team is joint to INRIA, the Ecole Normale Supérieure in Paris and the Ecole Nationale des Ponts et Chaussées. It is located in Sophia-Antipolis, rue d'Ulm in Paris and in Champs-sur-Marne. The scientific focus of the laboratory is the combined study of computer and biological vision. We think that a more detailed knowledge of the visual perception in humans and non-human

primates can have a potential impact on algorithm design, performance evaluation and cues on such questions as how to interface an artificial vision system with people, possibly handicapped. From a more general viewpoint and at another level, biological visual perception, in particular in non human primates and humans, is poorly understood and modeled. Making progress in

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this understanding is a grand scientific and philosophic challenge that frames our work. We conduct research in the following three main areas: I.1.1 Variational methods and partial differential equations for vision: We are interested in using variational methods and partial differential equations because they are the tools that allow us to • Mathematically model a large number of

computer vision problems such as segmentation, stereo, motion analysis or shape recognition.

• Study the existence and uniqueness of solutions.

• Design efficient algorithms for approximating those solutions.

Within this general framework, we are interested in the following two main areas • Feature integration, as seen from the

algorithmic and biological viewpoints. We are currently investigating:

o Shape from shading, to integrate occluding edges, shadows and textures. This work is done in the context of the theory of viscosity solutions.

o Stereo, a problem that also requires the integration of occluding contours, shadows and textures.

o The combination of stereo and motion.

o The combination of color, texture and motion for image segmentation.

• Shape representation and learning. We investigate the problem of acquiring geometric models from image sequences from the algorithmic and biologic viewpoints. We have proposed a number of mathematical formulations of this problem. We work on 3D deterministic and stochastic shapes representation and learning. Results can be included in the work on feature integration and are potentially useful for guiding segmentation and recognition.

I.1.2 Observing brain activity by functional imaging Brain imaging is a well-adapted tool to improve our knowledge of brain functioning, in particular of visual perception. Challenging computer vision problems can also be posed by this type of imagery. The evolution of technology gives access to ever increasing spatio-temporal resolutions, resulting in the measurement of cortical areas whose sizes are now compatible with our modelization tools. We focus on the following modalities, Magnetic Resonance (MR),

electroencephalography (EEG) and magneto-encephalography (MEG). In the case of MR, we use: • Functional magnetic resonance

images (fMRI). This is an indirect way of measuring brain activity through the Blood Oxygenation Level Dependent (BOLD) signal which is thought to be correlated with neuronal activity. Spatial resolution is, at best, of the order of one millimeter while temporal resolution is of the order of a tenth of a second.

• Diffusion tensor magnetic resonance imagery (DTMRI). This particular modality provides a measure of the diffusion of water molecules in tissues from which one can infer the geometry of the neural fibers connecting various areas of the brain (anatomical connectivity). This measure is also correlated to the electrical conductivity.

• Anatomical magnetic resonance imagery (aMRI). This can provide, through an algorithmic process called segmentation, a valuable geometric description of brain areas, e.g. the cortex, the white matter, the cerebrospinal fluid, etc.

EEG and MEG, which we note MEEG, provide measurements which are highly correlated to the electrical activity of the brain. The spatial resolution is of the order of one centimeter while the temporal resolution is of the order of one millisecond. These three modalities are complementary from the standpoint of their spatio-temporal resolutions and of the kind of information they can deliver. We work in the following six areas. • Spatio-temporal modeling of fMRI

signals to obtain more accurate and more detailed cortical activity maps than those provided by the currently available software packages.

• Spatio-temporal modeling of MEEG signals.

• The use of DTMRI to describe anatomical connectivity and improve the existing models of electrical conductivities currently used in MEEG.

• The analysis of the well-posedness of the inversed problem in MEEG, i.e. the existence and uniqueness of a particular brain activity that best accounts for the EEG/MEG measurements.

• The development of new numerical methods for solving the MEEG problem.

• The integration of these three modalities for studying visual perception in humans and non human primates.

I.1.3 Modeling cortical activity We use the results obtained within our second main research area to model the way

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the brain completes a visual perception task at a more general level than the "voxel" level. The spatio-temporal activity maps measured on humans and non human primates play an important role in this modeling which carries two main advantages. First we push forward the state of the art of the knowledge of the brain processes underlying visual perception and second we may discover interesting sources of inspiration for our work in computer vision. We also study cortical activity at a finer level than the "voxel" by fitting models of neurons assemblies to the measurements provided by fMRI, MEEG and possible micro-electrodes. We have two targets • The use of cortical columns models to

analyze the cortical activity measured by fMRI or MEEG goes beyond the use of the classical models of electric dipoles and opens up new perspectives as to what algorithmic complexity underlies this activity. This is also likely to have an impact on our understanding of the inverse problem in MEEG and therefore on the way we solve it.

• Such a description is closely related to the formalism of dynamic systems and, perhaps, partial differential equations. This is a fascinating possibility of connecting with our first main research area.

I.1.4 New results Here is a short list of new results (see the project specific activity report and WEB site for more details http://www-sop.inria.fr/odyssee/): Variational methods and partial differential equations for vision • Generalized Minimizing Flows

(G.Charpiat, R.Keriven, J.P.Pons, O.Faugeras)

• Implementing levelsets using finite element methods – application to cortex segmentation (T.Papadopoulo, J.Piovano)

• Image Statistics (G.Charpiat, R.Keriven, O.Faugeras)

• Shape Warping and Shape Statistics (G.Charpiat, R.Keriven, O.Faugeras, P.Maurel)

• Point correspondences and tangential velocities in the level set framework (O.Faugeras, G.Hermosillo, R.Keriven, JP.Pons)

• Reconciling landmarks and level sets (P.Maurel, R.Keriven, O.Faugeras)

• Multi-view stereo reconstruction and scene flow estimation (JP.Pons, R.Keriven, O.Faugeras)

• Digital Matting using Graph Cuts (O.Juan, R.Keriven)

• Motion segmentation using Graph Cuts (O.Juan, R.Keriven)

• Active Cuts (O.Juan, Y.Boykov) • Graphic Processor Unit algorithms

and data structures for Computer Vision (P.Labatut, R.Keriven, JP.Pons)

• Multiview stereovision using graph cuts (E.Cornet, R.Keriven)

• A Multiphase Level Set based Segmentation Framework with Pose Invariant Shape Prior (R.Deriche, M.Fussenegger, A.Pinz)

• Multi-region level set tracking with transformation invariant shape priors (R.Deriche, M.Fussenegger, A.Pinz)

• Tensor Processing for Texture and Color Segmentation (R.Deriche, R.De Luis-Garcia, M.Rousson, C.Alberola-López)

• Regularization of Mappings Between Implicit Manifolds of Arbitrary Dimension and Codimension (R.Deriche, N.Sochen)

• Vector-Valued Image Regularization with PDEs: A Common Framework for Different Applications (R.Deriche, D.Tschumperlé)

• Geodesic active regions and level set methods for motion estimation and tracking (R.Deriche, N.Paragios)

Observing and modeling the brain • Hemodynamic models investigation in

Optical Imaging (T.Deneux, I.Vanzetta, O.Faugeras, G.Masson)

• Blood flow recordings using high resolution Optical Imgaging (T.Deneux, I.Vanzetta, O.Faugeras)

• Use of nonlinear models in fMRI analysis (T.Deneux, O.Faugeras)

• EEG-fMRI fusion (T.Deneux, C.Bénar, O.Faugeras)

• Variational Approaches to the Estimation, Regularization and Segmentation of Diffusion Tensor Images (R.Deriche, C.Lenglet, M.Rousson, D.Tschumperlé)

• A Riemannian Approach to Anisotropic Filtering of Tensor Fields (C.Castano-Moraga, R.Deriche, C.Lenglet, JR.Alzola)

• Statistics on the Manifold of Multivariate Normal Distributions: Theory and Application to Diffusion Tensor MRI Processing (R.Deriche, O.Faugeras, C.Lenglet, M.Rousson)

• A Riemannian Approach to Diffusion Tensor Images Segmentation (R.Deriche, O.Faugeras, S.Lehéricy, C.Lenglet, M.Rousson, K.Ugurbil)

• A Riemannian Approach to Diffusion Tensors Estimation and Streamline-based Fiber Tracking (R.Deriche, O.Faugeras, S.Lehéricy, C.Lenglet, K.Ugurbil)

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• Diffeomorphic Matching of Symmetric Positive Definite Matrix Fields (R.Deriche, O.Faugeras, C.Lenglet, T.Papadopoulo)

• Activation Shifts from the Premotor to the Sensorimotor Territory of the Striatum during the Course of Motor Sequence Learning (H.Benali, J.Doyon, R.Deriche, O.Faugeras, S.Lehéricy, C.Lenglet, G.Sapiro, K.Ugurbil, P.F.VandeMoortele)

• Apparent Diffusion Coefficients from High Angular Resolution Diffusion Images: Estimation and Applications (R.Deriche, M.Descoteaux, E.Angelino, S.Fitzgibbons)

• A linear and regularized ODF estimation algorithm to recover multiple fibers in Q-Ball imaging (R.Deriche, M.Descoteaux, E.Angelino, S.Fitzgibbons)

• Forward and Inverse Boundary Element solutions for EEG and MEG (G.Adde, M.Clerc, O.Faugeras, J.Kybic, T.Papadopoulo, R.Keriven)

• Forward EEG problem using the volumic Finite Element approach and Implicit Meshes (M.Clerc, O.Faugeras, T.Papadopoulo)

• Fast Multipole Method for the forward problem of MEEG (M.Clerc, O.Faugeras, J.Kybic, T.Papadopoulo, R.Keriven)

• Skull conductivity estimation by Electrical Impedance Tomography (G.Adde, JM.Badier, M.Clerc, J.Kybic, T.Papadopoulo, S.Vallaghé)

• Cortical mapping (M.Clerc, J.Leblond, JP.Marmorat, T.Papadopoulo)

• Combined fMRI and DTI of the human low level visual cortex (JL.Anton,

R.Deriche, O.Faugeras, C.Lenglet, M.Roth, N.Wotawa)

• Motion direction selectivity in human visual cortex (E.Castet, O.Faugeras, N.Wotawa)

• Segmenting the cortical surface (JP.Pons, F.Ségonne)

• Active electrode compensation for intracellular recordings (R.Brette, Z.Pikowska, M.Rudolph, A.Destexhe, T.Bal)

Modeling cortical activity • Modeling a biologically-inspired

spiking retina model for the encoding of visual sequences (A.Wohrer, T.Vieville, P.Kornprobst)

• Biological motion recognition using fast brain-like mecanisms (I.Dimov, P.Kornprobst, T.Vieville)

• Building a link between PDE and biological networks (O.Faugeras, P.Kornprobst, T.Vieville)

• Bifurcation analysis of a cortical column model (F.Grimbert, O.Faugeras)

• Models of cortical activity at a mesoscopic scale (C.LaRota, M.Clerc, O.Faugeras)

• Neural Network Simulation on Graphic Processor Units (F.Bernhard, R.Keriven)

• A predictive bidimensional integrate-and-fire neuron model (R.Brette, W.Gerstner)

I.2. VisAGe Project (ex Atlantis) ENPC project Leaders: Nikos Paragios (until October), Florent Ségonne (from November) Visual perception refers to the ability of understanding the visual information that is provided by the environment. Such a mechanism integrates several human abilities and was studied by many researchers with different scientific origins including philosophy, physiology, biology, neurobiology, mathematics and engineering. In particular in the recent years an effort was made by mathematicians, statisticians and engineers to understand, formalize and finally reproduce mechanical visual perception systems able to see and understand the environment using computational theories. Such a task connects visual tasks with optimization processes, and the answer to the visual perception task corresponds to the lowest potential of a task-driven objective function. The Atlantis research group focused on three areas:

• Image Enhancement & Content-based Image Retrieval

• 3D Reconstruction, Urban modeling & Rendering & Virtual Environments

• Medical Image Analysis and Vascular Imaging

In November, Florent Ségonne replaced Nikos Paragios who left ENPC. The new group name (VisAGe for Vision, Apprentissage et Géométrie) expresses slight changes in the group competences, focused areas and application: Augmented Reality and Virtual Environments. I.2.1 Image Enhancement & Content-based Retrieval Image processing is an active research area. Recent developments on the hardware side have made possible, accessible and costless

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the acquisition of visual information either in the form of static images or in the form video. One can cite for example the case of the new generation of cellular phones which are all equipped with a camera. Such a development along with the proliferation of storage utilities and hardware like portable memories sticks, hard disks, etc. created a demand of image enhancement, denoising, completion, content-based representation and retrieval. Despite the advances on the hardware side, still low cost requirement constrain the quality of images that are acquired. While one can account on the evolution of hardware, intelligent post-acquisition techniques in the area of image processing can improve the quality of images presented to the user. Such a perspective can lead to efficient acquisition devises, is of low cost, not visible to the user and can have an evolving nature where novel more efficient solutions can be integrated in a straightforward fashion to the acquisition chip. Such a task is often called image denoising or enhancement and despite the fast that has been a well studied research domain of image processing still one cannot claim the existence of a golden standard algorithm. Furthermore one can claim that we experience a decade of digital era. Means of communication like test, audio, images and vide in the form of archives have been digitized. It is known from psychology that visual communication is the most effective way, therefore restoring images of low quality or partially destroyed - a task often called image inpainting - is of significant importance. Image description by content is another problem with numerous applications. The ability to store an enormous amount of information either in the form of images or video have created a necessity at a first glance for finding efficient ways of representing images according to their content as well as efficient searching engines that can retrieve from image/video databases events similar to the ones dictated according to the user input. Within this scope the following techniques have been/are studied within the group: • Image Enhancement through image

decomposition in structure & texture, (N.Azzabou & N.Paragios)

• Image Completion through Combinatorial Optimization, (C.Allène, R.Keriven & N.Paragios)

• Novel statistical methods for regression, classification and clustering, (J.-Y.Audibert)

• Content-based Image Retrieval, (J.-Y.Audibert, R.Keriven & N.Paragios)

I.2.2 3D Reconstruction, Urban modeling & Rendering & Virtual Environments Recovering structure from images or video is a core component of high-level vision. The task consists of determining the exact geometry of a 3D scene from 2D images that have been taken from different angles. Urban modeling is an example where such an application could have a significant importance. Given multiple views of large scale urban environments (for example through satellite imaging) one can reconstruct their geometry. Such information can be used as input to architects when aiming to modify, add or remove elements of the scene either on the appearance or on the geometry side so the environment remains human friendly, and ergonomic. It also can be used to create virtual environments that will allow studies on the possible consequences of certain modifications of the environment. The use of image is the most primitive approach to stereo reconstruction, an area of research that has been studied for a while now. Video is an additional cue that can improve the accuracy of reconstruction methods, while more recently 3D laser scanners have proven to be a robust approach towards determining the geometry of large scenes with limited accuracy. While such a problem seems to be tractable for the case of existing scenes, things become far more complicated when aiming to reconstruct impartial scenes. The case of reconstructing and augmenting archaeological sites is an example. While one can use all existing information to recover the existing geometry, an integration/augmentation of what we are seeing and prior knowledge on the structure of the scene are required to complete the missing parts. Furthermore, towards complete virtual environments one should be able to introduce the human factor. Examples consist of pointing to non-present parts of the scenes and being able to present to the end user all information with respect to these parts. This task is known as human-computer interaction. While the case of gesture understanding and interpretation through computational vision is the most elementary, visual face animations is the most challenging one where one would like to impose human presence according to geometrical and photo-realistic constraints. Within this research activity we explore • the use of static images with

unknown calibration parameters to recover the exact position of the camera in the real 3D world,

• the use of static images taken from different views to estimate depth elevation maps from aerial and satellite images,

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• the use of video from mobile observes to reconstruct real 3D dimensional scenes in layers of constant depth,

• the integration of multi-view visual and range/laser data to better address the reconstruction problem,

• the use of structural completion techniques to address reconstruction of partially destroyed environment using prior constraints on the geometry of the scene,

• the use of vision-based techniques towards virtual environments able to reproduce human behaviors, the case of face.

More precisely, the following points have been investigated: • Self-Determination of Observer’s

Position in Known Environments Using the Hough-Space, (P.Etyngier, J.-Y.Audibert, R.Keriven & N.Paragios)

• Satellite Imaging, Depth Elevation Maps and Free Form Deformations, (K.Karantzalos & N.Paragios)

• Recovering Scene Structure from Motion: Layers of Constant Depth through Combinatorial Techniques, (R.Dupont, R.Keriven & N.Paragios)

• Recovering Depth Elevation Maps and Scene Geometry through Monte-Carlo Sampling, (H.Papasaika & N.Paragios)

• Fusion of Laser Data and Multi-View Computational Stereo towards Reconstruction of Urban Scenes, (P.Etyngier, R.Dupon , R.Keriven & N.Paragios)

• Structural Completion through Combinatorial Optimization and Discrete Geometry, (C.Allène, M.Couprie, R.Keriven & N.Paragios)

• Graphics Processing Units and Multi-view stereo Reconstruction towards photo/expression-realistic facial animations, (C.Ghys & N.Paragios)

I.2.3 Medical Image Analysis and Vascular Imaging Cardiovascular diseases are the dominant cause of death worldwide. Late diagnosis often makes impossible proper treatment of the disease and therefore prevention and periodic monitoring is a crucial element of the health care. Late advances on the hardware side like non-invasive image acquisition could be used to provide certain amount of information that can be used towards computer aided diagnosis. There are two dominant problems in medical imaging, (i) segmentation that often consists of recovering an anatomical structure of particular interest, (ii) registration that consists of bringing two image modalities

that observe the same anatomy to the same pose (Computed Tomography and Magnetic Resonance are non-invasive modalities used to capture the state of the cardiac muscle at the same time). Proper functioning of the cardiac muscle involves the muscle itself that is contracting as well as the heart arteries that are the means of propagating the blood to the most distance tissues. Ultrasound images refer to a low cost portable modality that can be used to diagnose problems on the muscle through the estimation of the injection fraction, a quantity that refers to the blood that is sent to the distant tissues. Therefore, towards proper functioning of the heart muscle, real time segmentation of left ventricle is required that can be used to determine the state of the muscle since typical duration of the heart cycle is less than a second. Such a modality is of very low quality and processing using standard image processing techniques will fail due to the low signal to noise ratio. The use of prior knowledge on the structure to be recovered can be considered to address this limitation. Therefore building shapes models that account for the ventricle topology is an elementary step towards successful computer aided diagnosis. Once the muscle state has been verified, proper functioning of coronaries arteries, a tree of tubular structures used to transport back and forth blood between the heart and to the distance tissues is to be verified. While one can claim certain anatomical properties on the cardiac muscle that appear in common fashion to most of the individuals, coronaries are highly non-linear geometric structure/tree where neither the topology (branching) neither the state (diameters of the vessels) are known and therefore a different approach is to be developed. The following points have been investigated: • Combinatorial Optimization, Push-

Relabel Algorithm and Real-time Object Extraction, (N.Dixit, R.Keriven & N.Paragios)

• Modeling Shape Uncertainty and Variations in Medical Imaging with Applications to the Segmentation of the Epicardium, (M.Taron & N.Paragios)

• Segmentation and Implicit Tracking of the Left Ventricle in Echocardiographic Images, (N.Paragios)

• Particle Filters and Segmentation of Non-linear Tubular Structures: The Case of Coronaries, (C.Florin & N.Paragios)

I.2.4 New directions With the arrival of Florent Ségonne and the awaited return of Jean-Philippe Pons from a post-doctoral period, the group puts on a

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new name (VisAGe) and extends its domain of competence: • Computer Vision • Machine Learning and Learning

Theory • Discrete Geometry and deformable

models Toward a natural application of these competences, namely Augmented Reality and Virtual Environments, the group now focuses toward the following areas: 3D Object Reconstruction, Scene Modeling, Analysis, and Retrieval The team works on geometric models of specific 3D objects. They build on their current work on stereo reconstruction and scene flow estimation, and on recent developments in topology and discrete geometry to develop robust and accurate methods to reconstruct 3D scenes from calibrated or uncalibrated cameras. Jean-Philippe Pons’s work on multi-view stereo reconstruction outperformed several other technologies in a recent survey. The novelty of this work consists in a novel modeling of stereo matching with a global image-based similarity term. The latter perspective has many benefits: • no approximation either of the shape of

the object nor of the visibility is performed to compute the stereo discrepancy,

• the image similarity measure can be adapted to cope with different imaging conditions,

• the computations are compliant with a hardware implementation with graphic processor units (GPU).

Furthermore, the current research directions in this area include: • integrating shape and motion estimations

in order to obtain a spatio-temporal reconstruction of a dynamic scene from multiple video sequences,

• integrating 3D shape priors and classification methods to improve the identification of wellknown 3D models,

• significantly reducing the computation time with a GPU implementation,

• designing a robust and efficient method for topology-adaptive explicit deformable models, in order to overcome the computational expense of the level set method.

Learning Methods for Scene Understanding In addition, the group members bring their accurate knowledge of the machine learning

field. During past years, they have been participating in the core conferences of this field: COLT, NIPS and ICML. Their expertise concerns aggregation methods (such as AdaBoost), dimensionality reduction, compression schemes, graphs and kernel methods (such as SVM). They aim to help solve problems like human activity capture and classification and category-level object and scene recognition. In particular they design statistical tools dedicated to the latter. In category-level object and scene recognition, the state-of-the-art method can be sketched in the following way: (i) extracting patches of interest from images, (ii) partitioning the space of patches, (iii) representing an image by the number of patches in each set of the partition, and (iv) using a Support Vector Machine (SVM) on this representation to classify the images. This method has won most of the international recognition competitions. Nevertheless it disregards many key concepts. First an image is only viewed through a bag of patches for which no spatial relationship is specified and for which the 3D-nature of the scene represented by the image is not taken into account. Secondly, the way the space of patches is partitioned is not supervised. The clustering step is done independently from the contents of the images. To some extent it violates Vapnik’s statements: “do not try to solve as an intermediate step a task more difficult than the initial one” and “the simplest explanation is the best”. Thirdly the SVMs, which are arguably the best black box in machine learning, have several known drawbacks. The SVMs are impenetrable black boxes. No knowledge can be retrieved from them except the classification of data. Besides, it has been recently proved that the computation of the prediction proposed by a trained SVM is generally proportional to the number of learning points, which is a hurdle to real-time classification. Finally they are not flexible to the extent that it is difficult to introduce prior knowledge on the classification data (despite numerous attempts of the machine learning community to introduce it). The group approach is to design flexible statistical tools in which spatial relationships and features of different cognitive levels can be handled efficiently and meaningfully. They follow the theoretical and algorithmic works that have been initiated by the success of aggregated methods (also called boosting methods), such as AdaBoost. In particular, they propose a way to aggregate features such as, at each step, the generalization error of the aggregate decreases. The main advantages of such an iterative method are that:

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• it selects only relevant features and bases their prediction on them

• it is flexible to the extent that, through heuristics at the iteration step, it can handle smartly spatial relationships. As the SVMs, it can handle a high number of features. The difference here is that it controls the features that it used, while the SVMs widely combine them to

produce high-dimensional data in an abstract space.

• it is computationally efficient when used in a hierarchical structure

We believe that this supervised feature aggregation can be successful in learning the 3D-geometry of object, and more generally, in understanding a 3D-scene

I.3. COPRIN Project Joint Project between ENPC, INRIA, CNRS & UNSA - Leader: Jean-Pierre Merlet COPRIN is a joint project between Nice/Sophia-Antipolis University (UNSA), CNRS, ENPC and INRIA. Its scientific objective is to develop and implement systems solving and optimization algorithms based on constraints propagation methods, interval analysis and symbolic computation, with interval arithmetic as the primary tool. We are interested in real-valued constraint satisfaction problems, in optimization problems and in the proof of the existence of properties. Solutions will be searched within an infinite domain (called a box) which may be either continuous or mixed (i.e. for which some variables must belong to a continuous range while other variables may only have value within a discrete set). An important point is that we aim to find all the solutions within the domain as soon as the computer arithmetic will allow it: in other words we are looking for certified solutions. Our research aims to develop algorithms that can be used for any problem or are specific to a given class of problem, especially problems that are issued from application domains for which we have an internal expertise (such as mechanism theory and software engineering). Implementation of the algorithms will be performed within the frameworks of the generic software tool IcosAlias, currently under development, whose purpose is to allow one to design and test solving algorithms obtained as the combination of various software modules. IcosAlias will be based on the already existing libraries ICOS and ALIAS. As a theoretical complexity analysis of the solving algorithms is usually extremely difficult and as the usual worst case analysis leads to exponential complexity for problems that are not representative of the application cases we are considering, the efficiency of the algorithm will be experimentally evaluated through IcosAlias on various realistic bench examples. Dissemination is also an essential component of our activity as interval analysis based methods are not sufficiently known in the engineering and academic communities. I.3.1 Scientific Foundations

The scientific objective of the COPRIN project is to develop and implement systems solving and optimization algorithms based on constraints propagation methods, interval analysis and symbolic computation, with interval arithmetic as the primary tool. The results obtained with these algorithms are certified in the sense that all solutions will be obtained and can be calculated with an arbitrary accuracy. Furthermore some of our algorithms will allow us to deal with systems involving uncertain coefficients. A system will be constituted by a set of relations that may use all the usual mathematical operators and functions. We are interested in real-valued constraint satisfaction problems, in optimization problems and in the proof of the existence of properties. Solutions will be searched within a finite domain (called a box) which may be either continuous or mixed (i.e. for which some variables must belong to a continuous range while other variables may only have value within a discrete set). An important point is that we aim to find all the solutions within the domain as soon as the computer arithmetic will allow it: in other words we are looking for certified solutions. Our approach is to develop various operators that will be applied in sequence on a box: • exclusion operators: these operators

determine that there is no solution to the problem within a given box

• contractors: these operators may reduce the size of the box i.e. decrease the width of the allowed ranges for the variables

• existence operators: they allow one to determine that there is a unique solution within a given box and are usually associated to a numerical scheme that enables to compute this solution in a safe way

If a given box is not rejected by the exclusion operators and is not modified by the other operators, then we will bisect one of the variables in order to create two new boxes that will be processed later on. Methods for choosing the bisected variable are also clearly within the scope of the project. Our

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research aims to develop operators that can be used for any problem or are specific to a given class of problem, especially problems that are issued from application domains for which we have we have internally an expertise (such as mechanism theory and software engineering). Furthermore we will study symbolic computation based methods: • to develop a user-friendly interface

that will automatically generate an executable program, run it and return the result to the interface

• to analyze the semantics and syntax of the relations involved in a problem in order to automatically generate specific operators or to obtain a better interval evaluation of the relations (as interval arithmetic is very sensitive to the relations syntax)

• to allow the calculation of the solution with an arbitrary accuracy: certified interval solution will be obtained through a compiled program which is much more efficient than its symbolic computation equivalent and then a symbolic computation procedure will be used to calculate the solution up to the desired accuracy

I.3.2 Application Domains While the methods developed in the project may be used for a very broad set of application domains (for example a difficult problem in quantum mechanics has been addressed this year), it is clear that the size of the project does not allow all of them to be addressed. Hence we have decided to focus our applicative activities on two domains for which we have already an expertise: mechanism theory (including robotics) and software engineering. • mechanism theory: our research

focusses on optimal design and geometrical modeling of mechanisms, especially for the machine-tool industry, automotive suspensions and medical robotics. As some problems in mechanism theory and molecular chemistry are basically equivalent, they will also be addressed

• software engineering: our research focusses on the automatic generation of test data sets i.e. to generate input data so that a given step in a software module will be executed

Here is a short list of new results (see the project specific activity report and WEB site for more details http://www-sop.inria.fr/coprin/): • Optimal design of parallel robots with

respect to workspace and accuracy requirements (JP.Merlet, F.Hao, D.Daney)

• Cams coupled parallel robots (JP.Merlet)

• Accuracy indices (JP.Merlet) • Wire robot (JP.Merlet, D.Daney,

M.Gouttefarde, V.Ciauscu) • Calibration of a 4-RPR planar robot

(D.Daney, Y.Papegay, JP.Merlet) • Interval evaluation of kinematic

equations (D.Daney, T.Adelmar) • Interval analysis for control theory

(D.Daney, O.Pourtallier) • An Efficient and Safe Framework for

Solving Optimization Problems (Y.Lebbah, C.Michel, M.Rueher)

• Symbolic tools for modeling and simulation (Y.Papegay)

• Solver for distance equations (JP.Merlet)

• Uncertainty management in distance equations (C.Grandon, B.Neveu)

• Modal intervals (A.Goldsztejn) • Local search library (B.Neveu,

G.Trom-bettoni) • Local search methods for problems

with continuous variables (B.Neveu, R.Belkacem)

• Decomposition and solving of geometric constraints (B.Neveu, G.Trombettoni)

• Arc-consistency over continuous domains (G.Chabert, G.Trombettoni, B.Neveu)

• Efficient pruning technique based on linear relaxations (Y.Lebbah, C.Michel, M.Rueher)

• Bisection strategies (H.Batnini, C.Michel, M.Rueher)

II. OTHER ACTIVITIES II.1 Teaching The CERTIS has a strong involvement in the teaching activities at Ecole Nationale des Ponts et Chaussées. The CERTIS members are in charge of the first year Computer Science course, but also of half of the second year CS courses. They teach in the third year

CS master programs attended by ENPC students. In addition, they are in charge of one second year mathematics course and take part in the statistics course.

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The CERTIS members are also involved in teaching in different schools and universities such as ENS, ENS Cachan, X, UMLV, ESIEE,

UNSA, INT Evry, ENSTA, ESSI, ENTPE and ENSMP.

II.2 Publications The CERTIS sustains in 2005 a high level of scientific production: three books, two “Habilitation à Diriger des Recherches”, six PhDs, ten books chapters, eighteen papers in

main journals; and sixty one articles in the major international conferences of the domains.

II.3 International relations The CERTIS is involved in many international collaborations, both academic and industrial, through grants or student exchanges in Europe as well as in USA and Canada: Malmo, Copenhagen, Haïfa, Oxford, Lubljana, Prague, Utrecht, Mannheim, Debrecen, Dresden, Freiburg, Graz, Heidelberg, Lausanne, Leipzig, London, Plymouth,

Stockholm, Delft, Athens, Univ. Western Ontario, Saarland, Valladolid, Las-Palmas, Leuven, Univ. of North Carolina, Liverpool, Karlsruhe, Saarland, Zürich, Univ. of Minnesota, McGill Univ., AI Lab MIT, MGH Boston, CalTech, Siemens Corporate Research Princeton, Funetics S.a.r.l.

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III. CERTIS STAFF

Permanent Members Project Location Status AUDIBERT Jean-Yves VisAGe Champs ENPC/IPC BRETTE Romain Odyssee Paris ENS/MdC CLERC Maureen Odyssée Sophia ENPC/IPC DANEY David Coprin Sophia INRIA/CR DERICHE Rachid Odyssée Sophia INRIA/DR EL OUALI Khadija Certis Champs ENPC/Adm. assist. FAUGERAS Olivier Odyssée Sophia/Paris INRIA/DR KERIVEN Renaud Odyssée Champs/Paris ENPC/ICPC KORNPROBST Pierre Odyssée Sophia INRIA/CR LAFONT Marie-Cécile Odyssée Sophia INRIA/Admin. assistant MERLET Jean-Pierre Coprin Sophia INRIA/DR MICHEL Claude Coprin Sophia RNTL/Technical. staff MONDOU Brigitte Certis Champs ENPC/Admin. assistant NEVEU Bertrand Coprin Sophia ENPC/ICPC PAPADOPOULO Théodore Odyssée Sophia INRIA/CR PAPEGAY Yves Coprin Sophia INRIA/CR PARAGIOS Nikos VisAGe Champs ENPC/IPC POURTALLIER Odile Coprin Sophia INRIA/CR RUEHER Michel Coprin Sophia UNSA/Prof. SEGONNE Florent VisAGe Champs ENPC/IPC TROMBETTONI Gilles Coprin Sophia UNSA/Assist.Prof. VIEVILLE Thierry Odyssée Sophia INRIA/DR ZUZIA Corinne Coprin Sophia INRIA/Adm. assistant

Post-doct. Fellows Project Location BENARD Christian Odyssée Sophia GOUTTEFARDE Marc Coprin Sophia LAROTA Camilo Odyssée Sophia PONS Jean-Philippe VisAGe CalTech

PhD students Project Location ADDE Geoffray Odyssée Champs ALLENE Cédric VisAGe Champs AZZABOU Noura VisAGe Champs BATNINI Heikel Coprin Sophia CHABERT Gilles Coprin Sophia CHARIOT Alexandre Odyssée Champs CHARPIAT Guillaume Odyssée Paris DENEUX Thomas Odyssée Paris DESCOTEAUX.Maxime Odyssée Sophia DUPONT Romain VisAGe Champs ETYNGIER Patrick VisAGe Champs FASIELLO Irène Odyssée Paris FLORIN Charles VisAGe Champs GHYS Charlotte VisAGe Champs GOLDSZTEJN Alexandre Coprin Sophia GRANDON Carlos Coprin Sophia GRIMBERT François Odyssée Sophia JUAN Olivier Odyssée Champs LABATUT Patrick Odyssée Paris LENGLET Christophe Odyssée Sophia LOPEZ Lucero Odyssée Sophia MAUREL Pierre Odyssée Paris MOREELS Pierre Certis CalTech PIOVANO Jérome Odyssée Sophia PONS Jean-Philippe Odyssée Sophia RABARISOA Jaonary VisAGe Champs TARON Maxime VisAGe Champs TOUBOUL Jonathan Odyssée Paris

VALLAGHE Sylvain Odyssée Sophia WOHRER Adrien Odyssée Sophia WOTAWA Nicolas Odyssée Sophia Visiting scient. Project From Loc CIAUSU Viorel Coprin Iasi Sop. DONELAN Peter Coprin Wellington Sop. GUI Laura VisAGe Lausanne Chp. KARANTZALOS VisAGe Athens Chp. LEBBAH Yahia Coprin Oran Sop. MORAGA C. Odyssée Spain Sop. OTTAVIANO E. Coprin Cassino Sop. PAPASAIKA H. VisAGe Athens Chp. TSIGARIDAS E. Coprin Athens Sop.

Grad.Stud.Int. Project From Loc ADELMAR T Coprin IMERIR Sop. BELKACEM R Coprin UNSA Sop. CHARIOT A. Odyssée ESIEE Chp CORNET E. Odyssée ENS Lyon Chp De La Gorce M VisAGe MVA Chp HENRI P. Coprin ESSI Sop. HUJEIRI I. Odyssée UNSA Sop. LABATUT P. Odyssée ENS Par. RABARISOA J VisAGe MVA Chp

Stud.Interns Project From Loc BERNHARD F Odyssée Ec.Polytech. Par. CARAMEL B Odyssée ESSI Sop. DeRoquemaurel Odyssée Ec.Polytech. Chp HAUS S. VisAGe ENPC Chp MAIRAL J. Odyssée Ec.Polytech. Chp MEOUACHI Odyssée ENPC Sop. MONTIGNY D Odyssée UNSA Sop. REYNAUD A Odyssée ESSI Sop. RONDELA N Odyssée ESSI Sop. SIDDIQUIE B. VisAGe ITT Mombay Chp TEJ-EDDINE Odyssée ENPC Sop.

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IV. TEACHING R.Keriven, O.Juan, G.Adde, P.Maurel, P.Labatut, M.Taron, P.Etyngier, F.Ségonne, A.Chariot, J.Rabarisoa, Fundamentals in Computer Science, ENPC J.-Y.Audibert, Introduction to Statistics, ENPC J.-Y.Audibert, First year students’ projects, ENPC R.Keriven, N.Paragios, J.-Y.Audibert, F.Ségonne, Mathematics and Computer Science, ENPC R.Keriven, N.Paragios, F.Segonne, Image Processing, Computer Vision and Discrete Geometry, ENPC M.Clerc, Frequency analysis and applications, ENPC R.Keriven, R.Deriche, N.Paragios, Algorithmic Computer Vision, Master MPRI and MMFAI, ENS R.Keriven, N.Paragios, Augmented Reality, Master MVA, ENS Cachan O.Faugeras, Mathematical models for neuronal activity, Master MVA, ENS Cachan T.Papadopoulo, 3D Vision, Master MVA, ENS Cachan R.Keriven, Augmented Reality and Computer Vision, Master IFA, Marne La Vallée University R.Brette, Numerical Calculus (with Jean Ponce), Pre-Doctorat, ENS R.Deriche, Geometrical Advanced Techniques in Image Processing and Vision, Master STIC, UNSA T.Papadopoulo, 3D Vision, Master STIC, UNSA T.Viéville, Biological and computer models of motion perception, Master STIC, UNSA P.Kornprobst, Image Processing and Partial Differential Equations, ENSISA, EPU Sophia R.Deriche, Image Processing, INT Evry R.Brette, Students’ tutor, ENS

J.Piovano, A.Wohrer, S.Vallaghé, Computer Science (teaching assistants), Deug, UNSA F.Grimbert, Maple, CIV T.Deneux, P.Maurel, Computer Science (teaching assistants), Deug, Paris 7 University. I.Fasiello, G.Charpiat, Numerical Analysis (teaching assistants), Ecole Polytechnique. A.Chariot, Object Oriented Programming, ESTE A.Chariot, DLX Programming, ESIEE C.Allène, Computer architecture, ESIEE C.Allène, SQL Database, ESIEE C.Allène, Graphs and Algorithms, ESIEE C.Allène, Distributed Systems and Paralle-lism, ESIEE C.Allène, Object Oriented Programmation C++, ESTE C.Florin, Algèbre Linéaire pour la vision par ordinateur, applications en imagerie médicale, ISBS G.Chabert, H.Batnini, Computer Science, Deug, UNSA D.Daney, Medical Robotics, DESS Biomedical Engineering, UNSA J.P.Merlet, Robotics, ISIA O.Pourtallier, Game Theory and Optimization, Master OSE, ENSMP O.Pourtallier, Optimization, DESS IMAFA, UNSA M.Rueher, B.Neveu, G.Trombettoni, Y.Papagey, Constraint Programming, Master on Computer Science, UNSA M.Rueher, Constraint Programming, Databases and Logic Programming, UNSA G.Trombettoni, Computer Science, IUT R&T, Sophia

V. PUBLICATIONS

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V.1. Books & Dissertations N.Paragios, Y.Chen & O.Faugeras, Mathematical Models in Computer Vision: The Handbook, Springer, ISBN 0387263713, 2005. N.Paragios, O.Faugeras, T.Chan and C.Schnorr (eds). LNCS Proceedings, Variational, Geometric, and Level Set Methods in Computer Vision, Vol. 3752 , Softcover, ISBN: 3-540-29348-5, XI, 369 p, 2005. J.-P.Merlet, Parallel robots, Springer, 2005. N.Paragios, Variational and Statistical Me-thods in Computational Vision: Contributions & Applications, Habilitation a diriger des recherches, Universite de Nice-Sophia Antipolis, 2005. B.Neveu, Techniques de resolution de problemes de satisfaction de contraintes, Habilitation a diriger des recherches, Universite de Nice-Sophia Antipolis, 2005. G.Adde, Méthodes de Traitement d'Image Appliquées au Problème Inverse en Magnéto-

Electro-Encéphalographie., Ph.D. Thesis, Dec 2005, ENPC F.Segonne, Segmentation of Medical Images under Topological Constraints, Ph.D. Thesis, Dec 2005, MIT. J-P.Pons, Methodological and applied contributions to the deformable models method, Ph.D. Thesis, Nov 2005, ENPC. C.Chefd’hotel, Geometric methods in computer vision and image processings: contributions and applications, PhD Thesis, École Normale Supérieure de Cachan, April 2005. H.Batnini, Contraintes Globales et Techniques de Resolution pour les CSPs Continus, PhD Thesis, Universite de Nice-Sophia Antipolis, December 2005. A.Goldsztejn, Definition et Applications des Extensions des Fonctions Reelles aux Intervalles Generalises, PhD Thesis, Universite de Nice-Sophia Antipolis, November 2005.

V.2. Book Chapters N.Paragios, Curve Propagation, Level Set Methods & Grouping. In Mathematical Models in Computer Vision: The Handbook, N.Paragios, Y.Chen and O.Faugeras Eds, Springer, 2005. J-P.Pons, R.Keriven and O.Faugeras, Modelling Non-Rigid Dynamic Scenes from Multi-View Image Sequences. In Mathematical Models in Computer Vision: The Handbook, N.Paragios, Y.Chen and O.Faugeras Eds, Springer, 2005. E.Prados, O.Faugeras, Shape from Shading, In Mathematical Models in Computer Vision: The Handbook, N.Paragios, Y.Chen and O.Faugeras Eds, Springer, 2005. R.Deriche, D.Tschumperle, C.Lenglet, M.Rousson, Variational Approaches to the Estimation, Regularization and Segmentation of Diffusion Tensor Images, In Mathematical Models in Computer Vision: The Handbook, N.Paragios, Y.Chen and O.Faugeras Eds, Springer, 2005. N.Paragios, M.Taron, X.Huang, M.Rousson & D.Metaxas, On the Representation of Shapes

Using Implicit Functions. In Statistics and Analysis of Shapes. H.Krim and A.Yezzi Eds, Springer, 2005. G.Charpiat, O.Faugeras, R.Keriven, and P.Maurel, Approximations of shape metrics and application to shape warping and empirical shape statistics. In Statistics and Analysis of Shapes. H. Krim and A.Yezzi Eds, Springer, 2005. T.Brox, R.Boomgaard, F.Lauze, J.Weijer, J.Weickert, P.Mrazek, P.Kornprobst, Adaptive structure tensors and their applications, Springer, Berlin, 2005. M.Clerc, B.Atfeh, J.Leblond, L.Baratchart, J.-P.Marmorat, T.Papadopoulo, J.Partington, The Cauchy problem applied to cortical imaging: comparison of a boundary element and a bounded extremal problem, in : Brain Topography, C.M.D.Brandeis, T.Koenig (editors), 18, 2, Springer Science and Business Media B.V., October 2005. R.E.Azouzi, E.Altman, O.Pourtallier, Dynamic games, theory and applications, Springer, 2005, ch. 3, p. 57–77, Braess paradox and

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properties of wardropp equilibrium in some multiservice networks. M.Bossy, N.Ma¨ızi, G.Olsder, O.Pourtallier, E.Tanr´e, Dynamic games, theory and

applications, Springer, 2005, ch. 7, p. 135–159, Electricity prices in a game theory context.

V.3. Journal Papers J.-P.Pons, G.Hermosillo, R.Keriven, O.Faugeras, Maintaining the point correspondence in the level set framework. Journal of Computational Physics, in press. J.-P.Pons, R.Keriven, O.Faugeras, Multi-view stereo reconstruction and scene flow estimation with a global image-based matching score. International Journal of Computer Vision, in press. J.Kybic, M.Clerc, O.Faugeras, R.Keriven, T.Papadopoulo, Generalized head models for MEG/EEG: BEM beyond nested volumes. Physics in Medecine and Biology, in press. O.Juan, R.Keriven, G.Postelnicu, Stochastic Motion and the Level Set Method in Computer Vision: Stochastics Active Contours. International Journal of Computer Vision, in press. N.Paragios, R.Deriche, Geodesic Active Regions and Level Set Methods for Motion Estimation and Tracking. Computer Vision and Image Understanding, pp. 259-282, 2005. J.Kybic, M.Clerc, O.Faugeras, R.Keriven, T.Papadopoulo, Fast multipole acceleration of the MEG/EEG boundary element method. Physics in Medecine and Biology, 50:4695-4710. T.Abboud, M.Clerc, O.Faugeras, R.Keriven, J.Kybic, T.Papadopoulo, Integral Formulations for the EEG Problem. IEEE Transactions on Medical Imaging, jan 05. G.Charpiat, O.Faugeras, R.Keriven, Approximations of shape metrics and application to shape warping and empirical shape statistics. Foundations of Computational Mathematics, feb 2005. R.Brette, W.Gerstner, Adaptive exponential integrate-and-fire model as an effective description of neuronal activity, Journal of Neurophysiology 94, 2005, p. 3637–3642.

D.Tschumperle, R.Deriche, Vector-Valued Image Regularization with PDE’s: A Common Framework for Different Applications, IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 4, April 2005, p. 506–517 T.Viéville, An unbiased implementation of regularization mechanisms, Image and Vision Computing 23, 11, 2005, p. 981–998 D.Daney, B.Madeline, Y.Papegay, Choosing Measurement Poses for Robot Calibration with local Convergence Method and Tabu Search, International Journal of Robotic Research 24, 6, 2005, p. 501–518. A.Goldsztejn, A right-preconditioning process for the formal-algebraic approach to inner and outer estimation of AE-solution sets, Reliable Computing 11, 2005. Y.Lebbah, C.Michel, M.Rueher, D.Daney, J.-P.Merlet, Efficient and Safe Global Constraints for handling Numerical Constraint Systems, SIAM Journal on Numerical Analysis 42, 5, 2005, p. 2076–2097. Y.Lebbah, C.Michel, M.Rueher, A rigorous global filtering algorithm for quadratic constraints, Constraints Journal 10, 1, 2005, p. 47–65. M.Pavicic, J.-P.Merlet, B.McKay, N.Megill, Kochen-Specker vectors, J. Phys. A: Math Gen. 38, 7, February 2005, p. 1577–1592. J.-C.Régin, M.Rueher, An efficient and safe framework for solving optimization problems, J. of Computational and Applied Mathematics, in press J.-C.Régin, M.Rueher, Inequality-sum: a global constraint capturing the objective function, RAIRO-Operations research 39, 2, 2005, p. 123–139.

V.4. Conference Papers M.Hein, JY.Audibert, U.Von Luxburg, From graphs to manifolds - weak and strong pointwise consistency of graph Laplacians. In

Conference on Learning Theory (COLT), 470-485, June 2005.

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M.Hein, JY.Audibert, Intrinsic dimensionality estimation of submanifolds in R^d. In Proceedings of the 22nd International Conference on Machine Learning (ICML), August 2005. M.Taron, N.Paragios, M.-P.Jolly, Modelling Shapes with Uncertainties : Higher Order Polynomials, Variable Bandwidth Kernels and Non-Parametric Density Estimation. In Proc. 10th International Conference On Computer Vision, Beijing, October 2005. G.Charpiat, O.Faugeras, R.Keriven. Image statistics based on diffeomorphic matching. In Proc. 10th International Conference On Computer Vision, Beijing, October 2005. J-P.Pons, G.Charpiat, R.Keriven, O.Faugeras. Designing spatially coherent minimizing flows for variational problems based on active contours. In Proc. 10th International Conference On Computer Vision, Beijing, October 2005. F.Ségonne, E.Grimson, B.Fischl. A Genetic Algorithm for the Topology Correction of Cortical Surfaces . Information Processing in Medical Imaging, Glenwood Springs, 2005. P.Yu, F.Ségonne, X.Han, B.Fischl. Shape Analysis of Neuroanatomical Structures Based on Spherical Wavelets, In Human Brain Mapping 2005, Toronto P.Coupé, P.Hellier, N.Azzabou, C.Barillot. 3D Freehand Ultrasound Reconstruction based on Probe Trajectory, In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2005 C.Florin, N.Paragios and J.Williams. Particle Filters, a Quasi-Monte Carlo solution for segmentation of coronaries, In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2005 K.Karantzalos, N.Paragios. Higher Order Polynomials, Free Form Deformations and Optical Flow Estimation, IEEE International Conference on Image Processing (ICIP), 2005. J-P.Pons, R.Keriven, O.Faugeras. Modelling Dynamic Scenes by Registering Multi-View Image Sequences. In IEEE Conference in Computer Vision and Pattern Recognition (CVPR), 2005. S.Lim, A.Mittal, L.Davis, N.Paragios. Fast Illumination-invariant Background Subtraction using Two Views: Error Analysis,

Sensor Placement and Applications. In IEEE Conference in Computer Vision and Pattern Recognition (CVPR), 2005. N.Paragios, M.-P.Jolly, M.Taron and R.Ramaraj. Active Shape Models & Segmentation of the Left Ventricle in Echocardiography. In International Conference on Scale Space Theories and PDEs methods in Computer Vision, 2005. R.Dupont, P.Fuchs, R.Keriven. An Improved Calibration Technique for Coupled Single-Row Telemeter and CCD Camera. In 3-D Digital Imaging and Modeling (3DIM), 2005. G.Adde, M.Clerc, R.Keriven. Imaging Methods for MEG/EEG Inverse Problem. In Symposium on Noninvasive Functional Source Imaging, 2005. F. Ségonne, J.-P.Pons, E.Grimson, B.Fischl. A novel level set framework for the segmentation of medical images under topology control, Proc. ICCV Workshop on Computer Vision for Biomedical Image Applications - 2005 C.Florin, J.Williams, A.Khamene, N.Paragios, Registration of 3D angiographic and X-ray images using Sequential Monte Carlo sampling, Proc. ICCV Workshop on Computer Vision for Biomedical Image Applications - 2005 O.Juan, R.Keriven, Trimap Segmentation for Fast and User-Friendly Alpha Matting, IEEE Workshop on Variational, Geometric & Level Set Methods, Beijing, October 2005. K.Karantzalos, N.Paragios, Implicit Free-Form-Deformations for multi-frame Segmentation and Tracking, IEEE Workshop on Variational, Geometric & Level Set Methods, Beijing, October 2005. M.Taron, N.Paragios, M-P.Jolly. Uncertainty-driven Non-parametric Knowledge-based Segmentation: The Corpus Callosum Case. IEEE Workshop on Variational, Geometric & Level Set Methods, Beijing, October 2005. R.Dupont, N.Paragios, R.Keriven, P.Fuchs. Extraction of layers of similar motion through combinatorial techniques In International Workshop On Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), November 2005. R.Brette, M.Rudoph, Z.Pikowska, T.Bal, A.Destexhe, How to emulate doubleelectrode recordings with a single electrode? A new method of active electrode compensation. in:

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Neuroscience 2005 (SFN Annual meeting), 2005. M.Clerc, G.Adde, J.Kybic, T.Papadopoulo, J.-M.Badier, In vivo conductivity estimation with symmetric boundary elements, in: Proc. Joint Meeting of 5th International Conference on Bioelectromagnetism and 5th International Symposium on Noninvasive Functional Source Imaging, Minneapolis, May 2005. R.DeLuisGarcia, R.Deriche, M.Rousson, C.Alberola-López, Tensor Processing for Texture and Colour Segmentation, in: 14th Scandinavian Conference on Image Analysis, p.1117–1127, Joensuu, Finland, June 2005. P.Kornprobst, T.Viéville, I.Dimov, Could Early Visual Processes be Sufficient to Label Motions?, in : International Joint Conference on Neural Networks, 2005. P.Kornprobst, T.Viéville, I.Dimov, Could early visual processes label and segment motions?, in : 17th IMACS World Congress, Scientific Computation, Applied Mathematics and Simulation, 2005. S.Lehericy, C.Lenglet, J.Doyon, H.Benali, P.VandeMoortele, G.Sapiro, O.Faugeras, R.Deriche, K.Ugurbil, Activation Shifts from the Premotor to the Sensorimotor Territory of the Striatum during the Course of Motor Sequence Learning, in : 11th Annual Meeting of the Organization for Human Brain Mapping, Toronto, June 2005. C.Lenglet, R.Deriche, O.Faugeras, S.Lehericy, K.Ugurbil, A Riemannian Approach to Diffusion Tensors Estimation and Streamline-based Fiber Trackin, in : 11th Annual Meeting of the Organization for Human Brain Mapping, Toronto, June 2005. C.Lenglet, O.Faugeras, T.Papadopoulo, R.Deriche, Diffeomorphic Matching of Symmetric Positive Definite Matrix Fields, in : 2ème Congrés National de Mathématiques Appliquées et Industrielles, Evian, May 2005. C.Lenglet, M.Rousson, R.Deriche, O.Faugeras, S.Lehericy, K.Ugurbil, A Riemannian Approach to Diffusion Tensor Images Segmentation, in : Information Processing in Medical Imaging, p. 591–602, 2005. E.Prados, O.Faugeras, Shape from Shading: a well-posed problem ?, in : CVPR’2005,International Conference on Computer Vision and Pattern Recognition, San Diego, CA, USA, June 2005

D.Shafrir, N.Sochen, R.Deriche, Regularization of Mappings Between Implicit Manifolds of Arbitrary Dimension and Codimension, in : Variational, Geometric, and Level Set Methods in Computer Vision: Third International Workshop, VLSM, Lecture Notes in Computer Science, 3752, Springer-Verlag GmbH, p. 344, Beijing, China, October 2005. T.Viéville, P.Kornprobst, How fast-brain object categorization allows top-down processes of segmentation, in : European Conference on Visual Perception, 2005. T.Viéville, De la deuxième à la troisième dimension, in: (i)nterstices, 2005 T.Viéville, La grenouille et le robot, in: (i)nterstices, 2005 A.Wohrer, P.Kornprobst, T.Viéville, A biologically-inspired spiking retina model for the encoding of visual sequences, in : European Conference on Visual Perception, 2005. N.Wotawa, C.Lenglet, M.Roth, B.Nazarian, J.-L.Anton, R.Majhoub, R.Deriche, O.Faugeras, Combined fMRI and DTI of the human low level visual cortex, in : NeuroImage (HBM’05), Toronto, Canada, 2005. C.Florin, M.ElBawab, F.Azar, A New Method for Increasing the Flexibility of DICOM Tags Management, DICOM 2005 International Conference, Budapest H.Batnini, C.Michel, M.Rueher, Mind The Gaps: A New Splitting Strategy for Consistency Techniques, in : Proc. of CP’05, Eleventh International Conference on Principles and Practice of Constraint Programming, LNCS, 3709, Springer, p. 77–91, Sitges, Spain, 2005. H.Batnini, M.Rueher, C.Michel, Une strat´egie de r´esolution orient´ee par la topologie des CSP num´eriques, in : Actes JFPC’05 (1`eres Journ´ees Francophones de Programmation par Contraintes), p. 199–210, Lens, 2005. G.Chabert, G.Trombettoni, B.Neveu, Box-set consistency for interval-based constraint problems, in : 20th ACM Symposium on Applied Computing (SAC’05), p. 1439–1443, 2005. G.Chabert, G.Trombettoni, B.Neveu, IGC : une nouvelle consistance partielle pour les CSP continus, in : Actes JFPC’05 (1`eres Journ´ees Francophones de Programmation par Contraintes), p. 211–218, Lens, 2005.

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D.Daney, A.Andreff, Y.Papegay, Interval method for calibration of parallel robots: a vision-based experimentation, in : Computational Kinematics, Cassino, 2005. A.Goldsztejn, D.Daney, M.Rueher, P.Taillibert, Modal intervals revisited: a meanvalue extension to generalized intervals, in : Proc. of QCP-2005 (Quantification in Constraint Programming), Sitges, Spain, 2005. C.Grandon, B.Neveu, Using Constraint Programming for Solving Distance CSP with Uncertainty, in : Proc. of CP’05, Eleventh International Conference on Principles and Practice of Constraint Programming, p. doctoral program, Sitges, Spain, 2005. Y.Lebbah, C.Michel, M.Rueher, Efficient pruning technique based on linear relaxations, in : Global Optimization and Constraint Satisfaction, revised selected papers of COCOS’03, LNCS 3478, Springer, p. 1–14, 2005. Y.Lebbah, Safe reduction techniques for global optimization, in : INT’05: Interval methods and their applications, Copenhagen, August 25-27 2005. J.-P.Merlet, D.Daney, Dimensional synthesis of parallel robots with a guaranteed given accuracy over a specific workspace, in : IEEE Int. Conf. on Robotics and Automation, Barcelona, April 19-22 2005. J.-P.Merlet, D.Daney, Kinematics and synthesis of cams-coupled parallel robots, in : Computational Kinematics, Cassino, May 4-6 2005. J.-P.Merlet, Applications of interval analysis in robotics, in : INT’05: Interval methods and their applications, Copenhagen, August 25-27 2005.

J.-P.Merlet, Jacobian, manipulability, condition number and accuracy of parallel robots, in : ISRR, San Francisco, October 12-15 2005. J.-P.Merlet, The necessity of optimal design for parallel machines and a possible certified methodology, in : 2nd Int. Colloquium, Collaborative Research Centre 562, p. 7–20, Braunschweig, May 10-11 2005. J.-P.Merlet, Optimal design of robots, in : Robotics: Science and Systems, Boston, June 8-11 2005. J.-P.Merlet, Systems of distance equations: application to robotics, in : Workshop Proc. of Interval Analysis, Constraint Propagation, Application, p. 48–57, Sitges, October 1 2005. B.Neveu, C.Jermann, G.Trombettoni, Inter-block Backtracking : Exploiting the structure in continuous CSPs, in : Global Optimization and Constraint Satisfaction, revised selected papers of COCOS’03, LNCS, 3478, Springer, p. 15–30, 2005. B.Neveu, G.Trombettoni, F.Glover, IDW : un algorithme de recherche locale combinant intensification et diversification, in : Actes ROADEF’05, p. 288–289, Tours, 2005. Y.Papegay, D.Daney, Solving with Interval Analysis, in : Wolfram Technology Conference, Illinois, USA, 2005. Y.Papegay, Exploring Boardgame Strategies, in : Proceedings of the 7th International Mathematica Symposium, Perth, Western Australia, 2005. M.Rueher, Solving continuous constraint systems, in : 8th International Conference on Computer Graphics and Artificial Intelligence (3IA’2005), 2005. (Invited Talk)

V.5. Research Reports N.Azzabou, N.Paragios, F.Guichard, Application of Particle Filtering to Image Enhancement, Report 05-19, CERTIS, Dec 2005 N.Azzabou, N.Paragios, F.Guichard, Image Decomposition in Uniform and Patterned Regions towards Better Denoising, Report 05-18, CERTIS, Dec 2005 M.Taron, C.Ghys, N.Paragios, Uncertainties-driven Surface Morphing : The case of Photo-

realistic Transitions between Facial Expres-sions, Report 05-17, CERTIS, Dec 2005 O.Juan, and Y.Boykov. Active Cuts for Real-Time Graph Partitioning in Vision. Tech Report 655, CS Dept, University of Western Ontario, Nov 2005 F.Ségonne, J.P.Pons, B.Fischl, E.Grimson. A Novel Active Contour Framework. Muti-Component Level Set Evolution Under

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Topology Control CSAIL memo AIM-2005-020, MIT, November 2005. M.deLaGorce, N.Paragios. Hand Poste Estimation with Constrained Multi-hypotheses Gradient-Descent. Research Report 05-16, CERTIS, November 2005. F.Bernhard, R.Keriven. Spiking neurons and GPUs. Research Report 05-15, CERTIS, November 2005. E.Cornet. Contour based Multiview stereo and graph-cuts. Research Report 05-14, CERTIS, November 2005. J.Mairal, R.Keriven. A GPU implementation of variational stereo. Research Report 05-13, CERTIS, November 2005. P.Labatut, R.Keriven, J.-P.Pons. A GPU implementation of level set multiview stereo. Research Report 05-12, CERTIS, November 2005. P.Maurel, R.Keriven, O.Faugeras. Reconciling landmarks and level sets: geometric shape warping and matching using generalized gradients and correspondence-augmented implicit representations. Research Report 5726, INRIA, Oct 2005. Audibert J.-Y., Tsybakov A. Fast learning rates for plug-in estimators under the margin condition Prépublication, Laboratoire de Probabilités et Modèles Aléatoires, Universités Paris 6 et 7, 2005. C.Allène, N.Paragios. Image renaissance using discrete optimization and the alpha-expansion algorithm. Research Report 05-11, CERTIS, September 2005. M.Taron, N.Paragios, M-P.Jolly. Uncertainty-driven Non-parametric Knowledge-based Segmentation: The Corpus Callosum Case. Research Report 05-10, CERTIS, July 2005. K.Karantzalos, N.Paragios. Implicit higher order polynomials for motion estimation and tracking. Research Report 05-09, CERTIS, May 2005. M.Taron, N.Paragios, M-P. Jolly. Introducing error estimation in the shape learning framework : Spline based registration and non-parametric density estimator in the space of higher order polynomials.. Research Report 05-08, CERTIS, May 2005. N.Dixit, R.Keriven, N.Paragios. GPU-Cuts and Adaptive Object Extraction. Research Report 05-07, CERTIS, March 2005.

R.Dupont, N.Paragios, R.Keriven, P.Fuchs Spatio-temporal Motion Estimation and Segmentation in Layers: Robust Estimators, Markov Random Fields, Visual Grouping and Graph-based Optimization. Research Report 05-06, CERTIS, March 2005. G.Charpiat, J-Y.Audibert, O.Faugeras, R.Keriven. Diffeomorphic Matching and Image Statistics. Research Report 05-05, CERTIS, Feb 2005. O.Juan, R.Keriven. Unsupervised Segmen-tation for Digital Matting. Research Report 05-04, CERTIS, Feb 2005. C.Florin, N.Paragios, J.Williams. Monte-carlo Sampling, Particle Filters and Segmentation of Coronaries. Research Report 05-03, CERTIS, Jan 2005. T.Deneux, O.Faugeras, EEG-fMRI fusion of non-triggered data using Kalman filtering, research report number RR-5760, INRIA, November 2005. T.Deneux, O.Faugeras, Parameter estimation efficiency using nonlinear models in fMRI, research report number RR-5758, INRIA, November 2005. M.Descoteaux, E.Angelino, S.Fitzgibbons, R.Deriche, Apparent Diffusion Coefficients from High Angular Resolution Diffusion Imaging: Estimation and Applications”, research report number 5681, INRIA, September 2005 M.Descoteaux, E.Angelino, S.Fitzgibbons, R.Deriche, A linear and regularized ODF estimation algorithm to recover multiple fibers in Q-Ball imaging, research report number 5768, INRIA, November 2005. F.Grimbert, O.Faugeras, Analysis of Jansen’s model of a single cortical column, research report number RR-5597, INRIA, June 2005. I.Vanzetta, T.Deneux, G.Masson, O.Faugeras, Cerebral blood flow recorded at high sensitivity in two dimensions using high resolution optical imaging, research report number RR-5759, Inria, November 2005. T.Viéville, An abstract view of biological neural networks, research report number RR-5657, INRIA, August 2005. M.Bossy, N.Ma¨ızi, G.Olsder, O.Pourtallier, E.Tanr´e, Using game theory for the electricity market, research report number 5274, INRIA, 2005.

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VI. THESES VI.1. Member of committees R.Deriche and O.Faugeras: chairmen, reviewers or examiners in many HDR and PhD thesis committees R.Keriven: 2 PhD. P.Kornprobst: 1 PhD.

N.Paragios: 5 PhD. J-P.Merlet: 1 HDR and 2 PhD. M.Rueher: 4 HDR and 4 PhD. B.Neveu: 1 PhD.

VI.2. Ongoing theses A.Chariot, Processeurs Graphiques et Applications en Visions Algorithmique et Biologique, ENPC. G.Charpiat, Statistiques de courbes et d'images, ENS T.Deneux, Modélisation et IRMf, ENS. M.Descoteaux, IRM de diffusion à haute résolution angulaire , UNSA. I.Fasiello, Vision biologique, ENS Cachan. F.Grimbert, Modélisation d'ensembles de colonnes corticales et application à l'électro-encephalographie et à la magnéto-encephalographie, UNSA. P.Maurel, Statistiques de formes et croissance du cerveau, ENS. O.Juan, Extraction d’objets dans des séquences fixes et animées, ENPC. P.Labatut, Mouvement et formes tridimen-sionnelles, ENS. C.Lenglet, Processing and Analysis of Diffusion Tensor Magnetic Resonance Images, UNSA. L.Lopez-Pérez, Image Processing and PDE's on Non Flat Manifolds, UNSA J.Piovano, Extraction automatique de formes complexes : Application à la création de modèles anatomiques de la tête, UNSA. S.Vallaghé, Problèmes inverses en magnéto-électroencéphalographie, UNSA N.Wotawa, IRMf pour la rétinotopie et l'analyse de la perception du mouvement, UNSA.

A.Wohrer, Perception du mouvement par des neurones à impulsions, X. J.Touboul, Modèles stochastiques de réseaux de neurones biologiques, UNSA. G.Chabert, Langage de pilotage et de paramétrage d'algorithmes de résolution de contraintes par intervalles, UNSA. C.Grandon, Résolution de systèmes d'équations avec incertitudes, UNSA C.Allène, Structural Completion through Combinatorial Optimization and Discrete Geometry, UMLV. N.Azzabou, Image Enhancement through image decomposition in structure+texture, ENPC. R.Dupont, Segmentation vidéo et reconstruction tridimensionnelle: applications à l'urbanisme, ENPC. P.Etyngier, 3D reconstruction in urban environment, ENPC. J.Rabarisoa, Recherche par le contenu dans les bases de données images, ENPC. C.Florin, Particle Filters and Segmentation of Non-linear Tubular Structures: The Case of Coronaries, ENPC. C.Ghys, Multi-view stereo Reconstruction towards photo/expression-realistic facial animations, ENPC. M.Taron, Modelling Shape Uncertainty and Variations in Medical Imaging with Applications to the Segmentation of the Epicardium, ENPC.

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P.Moreels, Probalistic Models for Object Recognition, CalTech.

VI.3. Thesis defenses N.Paragios, Variational and Statistical Me-thods in Computational Vision: Contributions & Applications, HDR, UNSA. B.Neveu, Techniques de resolution de problemes de satisfaction de contraintes, HDR, UNSA. G.Adde, Méthodes de Traitement d'Image Appliquées au Problème Inverse en Magnéto-Electro-Encéphalographie., Ph.D, ENPC F.Ségonne, Segmentation of Medical Images under Topological Constraints, Ph.D, MIT.

J-P.Pons, Methodological and applied contributions to the deformable models method, Ph.D, ENPC. C.Chefd’hotel, Geometric methods in computer vision and image processings: contributions and applications, PhD, ENS Cachan. H.Batnini, Contraintes Globales et Techniques de Resolution pour les CSPs Continus, PhD, UNSA. A.Goldsztejn, Definition et Applications des Extensions des Fonctions Reelles aux Intervalles Generalises, PhD, UNSA.

VII. CONTRACTS AND GRANTS VII.1. Industrial grants N.Paragios, C.Ghys, PhD thesis “CIFRE” support, France Telecom Research & Technology. N.Paragios, N.Azzabou, PhD thesis “CIFRE” support, DxO, Image Enhancement, France. N.Paragios, C.Florin, PhD thesis support, Siemens Corporate Research, Princeton, USA. N.Paragios, M.Taron, PhD thesis support, Siemens Corporate Research, Princeton, USA.

J-P.Merlet, design of a wire-based measurement system, “Automotive Supplier” (confidential) B.Neveu, G.Trombettoni, new optimization algorithms, Amadeus. Y.Papegay, Improvement of the production of numerical flight simulators from models of aerodynamics, Airbus France.

VII.2. National Academic Grants F.Ségonne, R.Keriven, R.Dupont, N.Paragios, CNRS GIS: “Augmented Reality and Urban Modeling”, Polytechnicum Marne La Vallee M.Clerc, T.Papadopoulo, J-M.Badier, P.Marquis, Color Project: EEG++, “La Timone” Marseille hospital M.Clerc, O.Faugeras, R.Keriven, J.Leblond, J.Kybic, T.Papadopoulo, Large Dataset ACI: Obs-Cerv, Other INRIA projects, Pitié-Salpêtrière, “La Timone” Marseille hospital, Luminy, UNSA, CEA, Prague. O.Faugeras, P.Kornprobst, T.Vieville, Neuro-science ACI: DYNN Dynamic of biological plausible neuronal networks, Supaero

Toulouse, ENSEA, Université Paul Sabatier Toulouse, INSA Lyon. G.Charpiat, C.Chefd'hotel, O.Faugeras, G.Hermosillo, R.Keriven, CNRS specific action: Non-rigid registration, ENS Cachan, INT Evry, IMAG TIMC, INRIA Epidaure, INSA, IRISA, Louis Pasteur University, Paris V University, Paris XIII University. R.Keriven, A.Chariot, ANR RIAM: Wired Smart, UNSA, ENS, RealViZ, Mikros. R.Keriven, N.Paragios, ANR non thématique: Surf, ESIEE, Université Paris Dauphine.

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R.Keriven, ANR grid computing: GCPMF, ENPC-CERMICS, INRIA, Supelec, ECP, EDF, Pricing Partners, Misys, Calyon, Ixis-Cib C.Michel, M.Rueher, Y.Lebbah, D.Daney., ACI V3F: Validation and Verification of floating point numbers; LIFC, IRISA, CEA.

C.Michel, M.Rueher, Y.Lebbah., RNTL DANOCOPS Automatic Detection of non-conformities between a program and its specifications, Thales Systèmes Aeroportés, AXLOG ingénierie, LIFC, LSR.

VII.3. International Academic Grants M.Clerc, R.Deriche, O.Faugeras, R.Keriven, P.Kornprobst, T.Papadopoulo, T.Vieville, Marie Curie RTN: VisionTrain, INRIA, SISSA (Italy), Malmo University (Sweden), IT-Universitetet i Kobenhavn (Denmark), Technion (Israel), University of Oxford (United Kingdom), Univerza v Ljubljani (Slovenia), EPFL (Switzerland), CTU Prague (Czech Republic), Universiteit Utrecht (The Nederlands), University of Mannheim (Germany) M.Clerc, R.Deriche, O.Faugeras, R.Keriven, P.Kornprobst, T.Papadopoulo, T.Vieville, IST-FET biologically inspired systems IP: FACETS, U Bordeaux, CNRS (Gif-sur-Yvette and Marseille), U Debrecen, TU Dresden, U Freiburg, TU Graz, U Heidelberg, EPFL Lausanne, Funetics S.a.r.l. Lausanne, U London, U Plymouth, INRIA Sophia-Antipolis, KTH Stockholm N.Paragios, R.Keriven, PAI: Van Gogh, Delft University of Technology. N.Paragios, R.Keriven, PAI: De Stael, EPFL. M.Clerc, PAI Procope, Max Planck Institute, Leipzig M.Clerc, PAI Barrande, Center for Machine Perception, Prague

N.Paragios, O.Juan, student exchange support, University of Western Ontario, Canada. R.Deriche, O.Faugeras, Marie Curie Training Sites Fellowships: ImaVis, Saarland University, National University of Athens, Universidad de Valladolid, Graz University, Universidad Las-Palmas. R.Deriche, O.Faugeras, C.Lenglet, G.Charpiat, NSF-INRIA Proposal: Computational Tools for Brain Research, University of Minnesota R.Deriche, O.Faugeras, C.Lenglet, FFCR Canada Proposal: Biomedical Image Analysis, McGill University. R.Deriche, O.Faugeras, T.Papadopoulo, PAI Picasso, Las-Palmas University. D.Daney, J.P.Merlet, I.Emiris, PAI Platon, National Technical University of Athens. Coprin project, STREP Adventure: ARES, Scuola Superiore Sant-Anna Pisa (coordinator), ETH Zürich, Universitat de Barcelona.

VIII. MISSIONS AND CONFERENCES VIII.1. Conference Organisations O.Faugeras (CB), R.Keriven (PC), N.Paragios (PC), R.Deriche (PC), International Conference on Scale-Space Theories in Computer Vision N.Paragios (GC), R.Keriven (PC), R.Deriche (PC), IEEE Workshop on Variational, Geometric and Level Set Methods in Computer Vision O.Faugeras (CB), R.Deriche (AC), N.Paragios (AC), R.Keriven (PC), P.Kornprobst (PC), T.Papadopoulo (PC) European Conference on Computer Vision

R.Keriven (PC), N.Paragios (PC), R.Deriche (PC), T.Papadopoulo (PC), International Conference on Computer Vision R.Keriven (PC), T.Papadopoulo (PC), N.Paragios (PC), Inter-national Conference on Computer Vision and Pattern Recognition R.Keriven (PC), International Conference on Image Processing. R.Keriven (PC), International Conference on Pattern Regognition

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R.Keriven (GC), GDR MSPC Symposium on graph-cuts and discrete optimisation methods in Computer Vision R.Deriche (PC), International Symposium on Medical Imaging and Computing R.Deriche (PC), International Conference On Computer Analysis of Images and Patterns O.Faugeras (GC), Indian Conference on Computer Vision, Graphics and Image Processing. R.Deriche (AC), Congrès Francophone Recon-naissance des Formes et Intelligence Artificielle R.Deriche (GC), Workshop tunisien Traitement et Analyse de l’Information: Méthodes et Applications T.Viéville (PC), Inervis international workshop T.Viéville (GC), ACI-DYNN summer workshop N.Paragios (GC), IEEE Workshop on Video Proceedings in conjunction with the IEEE Computer Vision and Pattern Recognition Conference N.Paragios (PC), Medical Image Computing and Computer Assisted Intervention N.Paragios (PC), Computer Graphics International Conference N.Paragios (PC), Energy Minimization Methods in Computer Vision and Pattern Recognition N.Paragios (PC), International Symposium on Visual Computing

N.Paragios (PC), ACM Symposium on Solid Modeling and Applications N.Paragios (PC), IEEE Conference on Advanced Video and Signal-based Surveillance N.Paragios (PC), Traitement & Analyse D'Images: Methodes & Applications J-P.Merlet (GC), International Federation on the Theory of Machines and Mechanisms World Congress J-P.Merlet (PC), IEEE Int. Conf. on Robotics and Automation J-P.Merlet (PC), Int. Symp. on Robotics Research J-P.Merlet (PC), Workshop on Applications of interval analysis B.Neveu (PC), G.Trombettoni (PC), Journées Francophones de la Programmation par Contraintes B.Neveu (PC), International Workshop on Preferences and Soft Constraints D.Daney (PC), Journées Nationales de la Recherche en Robotique. Y.Papegay (PC), Journées Nationales de Calcul Formel M.Rueher (PC), G.Trombettoni (PC), International Conference on Integration of AI and OR Techniques in Constraint Program-ming for Combinatorial Optimization Problems M.Rueher (PC), Constraint Programming Conference.

VIII.2. Invited talks R.Keriven, O.Juan, GDR MSPC Symposium on graph-cuts and discrete optimisation methods in Computer Vision, Paris R.Keriven, ENS Ponce group seminar, Paris R.Deriche, International Conference of Computer Systems and Information Technology, Algiers R.Deriche, lectures at USTHB, Algiers M.Clerc, Workshop on Autosimilarity and Applications, Toulouse

M.Clerc, GREMAQ seminar, Toulouse R.Brette, workshop on single neuron modelling, EPFL, Lausanne R.Brette, workshop on neural simulation, Graz, Austria P.Kornprobst, GDR ISIS and MACS meeting on PDEs in image processing, Paris.

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N.Paragios, O.Faugeras, GDR MSPC meeting on mathematical problems in image processing, Paris. N.Paragios, Service Hospitalier Frédéric Joliot, Paris N.Paragios, Ecole Normale Superieure, Paris N.Paragios, Cornell Medical School, New York N.Paragios, Rutgers University, Piscataway Ecole Federale Polytechnique de Lausanne

M.deLaGorce, vision group seminar, TU Delft C.Ghys, vision group seminar, TU Delft A.Goldsztejn, French working group MEA seminar B.Neveu, Franco-Japanese Workshop on Constraint Programming, Le Croisic, France. M.Rueher, International Conference on Computer Graphics and Artificial Intelligence, Limoges

VIII.3. Conference communications JY.Audibert, Conference on Learning Theory, Bertinoro, Italy JY.Audibert, International Conference on Machine Learning, Bonn Germany J-P.Pons, G.Charpiat, O.Faugeras, R.Keriven, M.Taron, N.Paragios, International Conference On Computer Vision, Beijing. F.Ségonne, N.Wotawa, C.Lenglet, O.Faugeras, R.Deriche, Human Brain Mapping, Toronto C.Florin, N.Paragios, N.Azzabou, International Conference on Medical Image Computing and Computer Assisted Intervention, Palm Springs, USA N.Paragios, IEEE International Conference on Image Processing, Genova J-P.Pons, R.Keriven, O.Faugeras, N.Paragios, IEEE Conference in Computer Vision and Pattern Recognition, San Diego N.Paragios, M.Taron, International Conference on Scale Space Theories and PDEs methods in Computer Vision, Hofgeismar, Germany R.Dupont, R.Keriven. 3-D Digital Imaging and Modeling, Otawa, Canada. G.Adde, M.Clerc, R.Keriven, T.Papadopoulo, Symposium on Noninvasive Functional Source Imaging, Minneapolis F. Ségonne, J.-P.Pons, C.Florin, N.Paragios, Workshop on Computer Vision for Biomedical Image Applications, Beijing O.Juan, R.Keriven, R.Deriche, N.Paragios, M.Taron, IEEE Workshop on Variational, Geometric & Level Set Methods, Beijing

R.Dupont, N.Paragios, R.Keriven, International Workshop On Energy Minimization Methods in Computer Vision and Pattern Recognition, St Augustine, USA R.Brette, Neuroscience SFN Annual meeting, Washington, DC R.Deriche, M.Rousson, Scandinavian Conference on Image Analysis, Joensuu, Finland P.Kornprobst, T.Viéville, International Joint Conference on Neural Networks, Montréal P.Kornprobst, T.Viéville, IMACS World Congress, Scientific Computation, Applied Mathematics and Simulation, Paris C.Lenglet, O.Faugeras, T.Papadopoulo, R.Deriche, Congrés National de Mathématiques Appliquées et Industrielles, Evian F.Ségonne, C.Lenglet, M.Rousson, R.Deriche, O.Faugeras, Information Processing in Medical Imaging, Glenwoods Springs, USA A.Wohrer, T.Viéville, P.Kornprobst, European Conference on Visual Perception, Coruna, Spain C.Grandon, H Batnini, B.Neveu, G.Trombettoni, International conference on Principles and Practice of Constraint Programming, Sitges, Spain D.Daney, J-P.Merlet, IEEE ICRA, Barcelona. D.Daney, International Workshop on Computer Algebra in Scientific Computing, Kalamata, Greece.

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A. Goldsztejn, workshop QCP2005, Sitges, Spain. J-P.Merlet, Y. Papegay, Computational Kinematics workshop, Cassino, Italy J-P.Merlet, Int. Colloquium, Braunschweig J-P.Merlet, Robotics: Science and Systems, MIT, Boston J-P.Merlet, Int. Symp. on Robotics Research, San Francisco J-P.Merlet, Interval methods and their applications, Copenhagen J-P.Merlet, Applications of interval analysis Sitges, Spain. Y.Papegay, International Mathematica Symposium, Perth, Australia Y.Papegay, Wolfram 2005 Technology Conference, Urbana Champaign, Illinois, USA

M.Rueher, International Conference on Integration of AI and OR Techniques in Constraint Program-ming for Combinatorial Optimization Problems, Prague O.Pourtallier, Optimization days, GERAD Mont-real H.Batnini, G.Chabert, B.Neveu, G.Trombettoni, Journees Francophones de programmation par contraintes, Lens. D.Daney, Journees Nationales de la Recherche en Robotique, Guidel B.Neveu, congres de la Societe Francaise de Recherche Operationnelle et d’Aide a la Decision, Tours B.Neveu, G.Trombettoni, G.Chabert, AS Contraintes géométriques workshops, Saint-Ouen and Marseille. M.Rueher, ACI Securite Workshop

VIII.4. Students exchange VIII.4.1 Outgoing O.Juan, University of Western Ontario, Canada, 6 months M.deLaGorce, Delft Institute of Technology, one month C.Ghys, Delft Institute of Technology, one month

M.Taron, Ecole Polytechnique Federale de Lausanne, one month N.Azzabou, Ecole Polytechnique Federale de Lausanne, one month

VIII.4.2 Incoming L.Gui, Ecole Polytechnique Federale de Lausanne, one month

C.C.Moraga, Valladolid, Spain, six months

IX. SERVICES TO THE SCIENTIFIC COMMUNITY R.Keriven, reviewer for the Research Grants Council of Hong Kong R.Deriche, expert member of the scientific committee of the Marie-Curie actions for young researcher mobility. R.Deriche, member of the Editorial Board of the International Journal of Computer Vision R.Deriche, member of the Expert Commission CS 61 Génie informatique, automatique et traitement du signal of UNSA

O.Faugeras, member of the Institut de France, Académie des Sciences. O.Faugeras, chairman of the scientific board of the Institut Français du Pétrole R.Brette, a member of the editorial board of Cognitive Neurodynamics. T.Papadopoulo, member of the Software deve-lopment committee of the Sophia-Antipolis INRIA Research Unit.

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T.Viéville, scientific animator of the )i(nterstices project N.Paragios, member of the Editorial Board and associate editor of the International Journal of Computer Vision N.Paragios, reviewer for the Agence Nationale de la Rechechre, Swiss Research Council, Dutch Research Council, Hong Kong Research Council

J.P.Merlet, associate editor of Mechanism and Machine Theory J.P.Merlet, associate editor of IEEE Transactions on Robotics M.Rueher, a member of the national committee CNU 27 and president of the Expert Commission 27 of UNSA

X. SEMINARS Odyssee seminar 01/02/05, Long Quan, Hong Kong University of Science and Technology 02/16/05, Agnès Aubert, Université de Lausanne 02/16/05, Robert Costalat Institut de Physiologie Univ. Paris 6 03/02/05, Alain Prochiantz, Dept. Biologie, ENS 04/08/05, Frederic Meunier, Institut d'Informatique et Mathématiques Appliquées de Grenoble 04/20/05, Alain Destexhe, Unité de Neurosciences Intégratives et Computationnelles, Gif

05/04/05, Boris Gutkin, University College London 06/23/05, Hezy Yeshurun, Tel Aviv University 06/28/05, Nicolas Brunel, Laboratoire de Neurophysique et Physiologie ENS 11/09/05, Rudy Guyonneau, CERCO Toulouse 11/23/05, François Baccelli, ENS Paris / INRIA 11/29/05, Vladimir Kolmogorov, Univ of London 12/14/05, Bertrand Thirion, CEA Orsay SHFJ 12/15/05, Bruno Cessac, Institut non-lineaire de Nice

VisAGe seminar 02/01/05, Konstantinos Karantzalos, Univ Athens 02/01/05, Olivier Buisson, Departement Recherche et Etudes, Institut National de l'Audiovisuel 03/08/05, Hugues Talbot, ESIEE 03/30/05, Dimitris Metaxas, Rutgers University

04/25/05, Benedicte Bascle, France Telecom R&D 09/01/05, Atsushi Imiya, Chiba University, Japan 10/03/05, Laura Gui, EPFL, Lausanne 10/11/05, Joachim Weickert, U. of Saarland, Germany

COPRIN seminar 04/08/05, Olivier Anglada, LIF, Marseille 05/20/05, Philippe Trébuchet, LIP6, Paris

05/17/05, Martine Cébério, Univ. El Paso, Texas 07/05/05, Dominique Michelucci, Univ. Bourgogne, Dijon

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11/09/05, Ernest Gardenyes, Univ. Barcelona, Spain 11/09/05, Luc Jaulin, ENSIETA, Brest

11/09/05, Peter Donolan, Victoria University of Wellington, New Zealand 12/15/05, Khalil Djelloul, LIF, Marseille

XI. SOFTWARES R.Keriven, O.Juan, G.Adde. WinLib, multiplatform C++ 2D/3D graphical library for education. R.Keriven, LsLib, C++ Level Set library. G.Adde, OpenMeeg, a multiplatform C++ forward and inverse solver for the Magneto-Electro-Encephalo-graphy problem. O.Juan, SmallMatrix, a fast multiplatform C++ library for small dense matrices. T.Vieville, P.Kornprobst, VisStim, A software to create parameterised standard video sequences used in psychophysics

A.Goldsztejn, D.Daney, BIASK, an implementation of Kaucher arithmetic J-P.Merlet, G.Chabert, D.Daney, Y.Papegay, O.Pourtallier, The ALIAS library (Algorithms Library of Interval Analysis for Systems) G.Chabert, D.Daney, C.Grandon, J-P.Merlet, B.Neveu, G.Trombettoni, ICOSALIAS, constraint solving platfom. B.Neveu, G.Trombettoni: INCOP , C++ Local Search Library

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ACRONYMS AC Area Chair CalTech California Institute of Technology CB Conference Board Member CEA Commissariat à l'Etude Atomique CERCO Centre de Recherche Cerveau et Cognition CNRS Centre National Recherche Scientifique ENPC Ecole Nationale des Ponts et Chaussées ENS Ecole Normale Supérieure ENTPE Ecole Nationale des Travaux Publics de l'Etat EPFL Ecole Polytechnique Fédérale de Lausanne ESIEE École Supérieure d'Ingénieurs en Électronique et Électrotechnique ESTE Ecole Supérieure de Technologie Electronique ETH Eidgenössische Technische Hochschule (Federal Institute of Technology) FFCR Fonds France Canada pour la Recherche GC General Chair GIS Groupement d'Intérêt Scientifique IMAG Institut d’Informatique et Mathématiques Appliquées de Grenoble INRIA Institut National de Recherche en Informatique et en Automatique INSA Institut National des Sciences Appliquées INT Institut National des Télécommunications IRISA Institut de Recherche en Informatique et Systèmes Aléatoires ISBS Institut Superieur des BioSciences Paris IST Information Societies Technologies IUT Universitaire de Technologie KTH Kungliga Tekniska Högskolan (Royal Institute of Technology) ale LIFC Laboratoire d'Informatique de l'Université de Franche-Comté LIRMM Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier LSR Laboratoire Logiciels Systèmes Réseaux MIT Massachusetts Institute of Technology PAI Programme d'Action Intégrée PC Program Commitee Member RIAM Recherche et Innovation dans l'Audiovisuel et le MultiMédia RNTL Réseau National des Technologies Logicielles TIMC Techniques de l'Imagerie,de la Modelisation et de la Cognition UMLV Université Marne la Vallée UNSA Université Nice Sophia-Antipols X Ecole Polytechnique