Publications

2017

• Déborder l'expérience pour laisser une trace. Vidéophénoménographie d'un rappeur
  
  • Kneubühler Marine
  , 2017, pp.147-242.
• LISP EID Block
  
  • Iannone Luigi
  • Lewis Darrel
  • Meyer Dave
  • Fuller Vince
  , 2017.
• Conception d'absorbants à base de métasurfaces et Application de la Transformation d'Espace pour le contrôle du rayonnement d’une antenne imprimée
  
  • Lepage A. C.
  • Begaud Xavier
  , 2017.
• Les Communications par Fibres Optiques : La Fin de l'Age de Cuivre
  
  • Gallion Philippe
  , 2017, pp.8.
• Décomposition de séries temporelles d'images SAR pour la détection de changements
  
  • Lobry Sylvain
  • Denis L.
  • Zhao Weiying
  • Tupin Florence
  Traitement du Signal, Lavoisier, 2017.
• Dynamic mitigation of EDFA power excursions with machine learning
  
  • Huang Yishen
  • Gutterman Craig L.
  • Samadi Payman
  • Cho Patricia B.
  • Samoud Wiem
  • Ware Cédric
  • Lourdiane Mounia
  • Zussman Gil
  • Bergman Keren
  Optics Express, Optical Society of America - OSA Publishing, 2017, 25 (3), pp.2245 - 2258. Dynamic optical networking has promising potential to support the rapidly changing traffic demands in metro and long-haul networks. However, the improvement in dynamicity is hindered by wavelength-dependent power excursions in gain-controlled erbium doped fiber amplifiers (EDFA) when channels change rapidly. We introduce a general approach that leverages machine learning (ML) to characterize and mitigate the power excursions of EDFA systems with different equipment and scales. An ML engine is developed and experimentally validated to show accurate predictions of the power dynamics in cascaded EDFAs. Recommended channel provisioning based on the ML predictions achieves within 1% error of the lowest possible power excursion over 94% of the time. We also showcase significant mitigation of EDFA power excursions in super-channel provisioning when compared to the first-fit wavelength assignment algorithm (10.1364/OE.25.002245)
  DOI : 10.1364/OE.25.002245
• Parameter estimation of perfusion models in dynamic contrast-enhanced imaging: a unified framework for model comparison
  
  • Romain Blandine
  • Rouet Laurence
  • Ohayon Daniel
  • Lucidarme Olivier
  • d'Alché-Buc Florence
  • Letort Véronique
  Medical Image Analysis, Elsevier, 2017, 35, pp.360--374. Patients follow-up in oncology is generally performed through the acquisition of dynamic sequences of contrast-enhanced images. Estimating parameters of appropriate models of contrast intake diffusion through tissues should help characterizing the tumour physiology. However, several models have been developed and no consensus exists on their clinical use. In this paper, we propose a unified framework to analyse models of perfusion and estimate their parameters in order to obtain reliable and relevant parametric images. After defining the biological context and the general form of perfusion models, we propose a methodological framework for model assessment in the context of parameter estimation from dynamic imaging data: global sensitivity analysis, structural and practical identifiability analysis, parameter estimation and model comparison. Then, we apply our methodology to five of the most widely used compartment models (Tofts model, extended Tofts model, two-compartment model, tissue-homogeneity model and distributed-parameters model) and illustrate the results by analysing the behaviour of these models when applied to data acquired on five patients with abdominal tumours. (10.1016/j.media.2016.07.008)
  DOI : 10.1016/j.media.2016.07.008
• Demystifying the asymptotic behavior of global denoising
  
  • Houdard Antoine
  • Almansa Andrès
  • Delon Julie
  Journal of Mathematical Imaging and Vision, Springer Verlag, 2017. In this work, we revisit the global denoising framework recently introduced by Talebi and Milanfar. We analyze the asymptotic behavior of its mean-squared error restoration performance in the oracle case when the image size tends to infinity. We introduce precise conditions on both the image and the global filter to ensure and quantify this convergence. We also make a clear distinction between two different levels of oracle that are used in that framework. By reformulating global denoising with the classical formalism of diagonal estimation, we conclude that the second-level oracle can be avoided by using Donoho and Johnstone’s theorem, whereas the first-level oracle is mostly required in the sequel. We also discuss open issues concerning the most challenging aspect, namely the extension of these results to the case where neither oracle is required. (10.1007/s10851-017-0716-6)
  DOI : 10.1007/s10851-017-0716-6
• Formal Semantics of Behavior Specifications in the Architecture Analysis and Design Language Standard
  
  • Besnard Loic
  • Gautier Thierry
  • Le Guernic Paul
  • Guy Clément
  • Talpin Jean-Pierre
  • Larson Brian
  • Borde Etienne
  , 2017. (10.1007/978-981-10-4436-6_3)
  DOI : 10.1007/978-981-10-4436-6_3
• Robust Downbeat Tracking Using an Ensemble of Convolutional Networks
  
  • Durand Simon
  • Bello Juan Pablo
  • David Bertrand
  • Richard Gael
  IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2017, 25 (1), pp.76-89. <div><p>In this paper, we present a novel state of the art system for automatic downbeat tracking from music signals. The audio signal is first segmented in frames which are synchronized at the tatum level of the music. We then extract different kind of features based on harmony, melody, rhythm and bass content to feed convolutional neural networks that are adapted to take advantage of the characteristics of each feature. This ensemble of neural networks is combined to obtain one downbeat likelihood per tatum. The downbeat sequence is finally decoded with a flexible and efficient temporal model which takes advantage of the assumed metrical continuity of a song. We then perform an evaluation of our system on a large base of 9 datasets, compare its performance to 4 other published algorithms and obtain a significant increase of 16.8 percent points compared to the second best system, for altogether a moderate cost in test and training. The influence of each step of the method is studied to show its strengths and shortcomings.</p></div> (10.1109/TASLP.2016.2623565)
  DOI : 10.1109/TASLP.2016.2623565
• On some bounds for symmetric tensor rank of multiplication in finite fields
  
  • Ballet Stéphane
  • Pieltant Julia
  • Rambaud Matthieu
  • Sijsling Jeroen
  , 2017, 686, pp.93 - 121. We establish new upper bounds about symmetric bilinear complexity in any extension of finite fields. Note that these bounds are not asymptotical but uniform. Moreover, we discuss the validity of certain published bounds. (10.1090/conm/686/13779)
  DOI : 10.1090/conm/686/13779
• Planck intermediate results. LI. Features in the cosmic microwave background temperature power spectrum and shifts in cosmological parameters
  
  • Aghanim N.
  • Akrami Yashar
  • Ashdown M.
  • Aumont J.
  • Ballardini M.
  • Banday A.J.
  • Barreiro R.B.
  • Bartolo N.
  • Basak S.
  • Benabed K.
  • Bersanelli M.
  • Bielewicz P.
  • Bonaldi A.
  • Bonavera L.
  • Bond J.R.
  • Borrill J.
  • Bouchet F.R.
  • Burigana C.
  • Calabrese E.
  • Cardoso J.F.
  • Challinor A.
  • Chiang H.C.
  • Colombo L.P.L.
  • Combet C.
  • Crill B.P.
  • Curto A.
  • Cuttaia F.
  • de Bernardis P.
  • de Rosa A.
  • de Zotti G.
  • Delabrouille J.
  • Di Valentino E.
  • Dickinson C.
  • Diego J.M.
  • Dore O.
  • Ducout A.
  • Dupac X.
  • Dusini S.
  • Efstathiou G.
  • Elsner F.
  • Ensslin T.A.
  • Eriksen H.K.
  • Fantaye Y.
  • Finelli F.
  • Forastieri F.
  • Frailis M.
  • Franceschi E.
  • Frolov A.
  • Galeotta S.
  • Galli S.
  • Ganga K.
  • Genova-Santos R.T.
  • Gerbino M.
  • Gonzalez-Nuevo J.
  • Gorski K.M.
  • Gruppuso A.
  • Gudmundsson J.E.
  • Herranz D.
  • Hivon E.
  • Huang Z.
  • Jaffe A.H.
  • Jones W.C.
  • Keihanen E.
  • Keskitalo R.
  • Kiiveri K.
  • Kim J.
  • Kisner T.S.
  • Knox L.
  • Krachmalnicoff N.
  • Kunz M.
  • Kurki-Suonio H.
  • Lagache G.
  • Lamarre J.M.
  • Lasenby A.
  • Lattanzi M.
  • Lawrence C.R.
  • Le Jeune M.
  • Levrier F.
  • Lewis A.
  • Lilje P.B.
  • Lilley M.
  • Lindholm V.
  • Lopez-Caniego M.
  • Lubin P.M.
  • Ma Y.Z.
  • Macias-Perez J.F.
  • Maggio G.
  • Maino D.
  • Mandolesi N.
  • Mangilli A.
  • Maris M.
  • Martin P.G.
  • Martinez-Gonzalez E.
  • Matarrese S.
  • Mauri N.
  • Mcewen J.D.
  • Meinhold P.R.
  • Mennella A.
  • Migliaccio M.
  • Millea M.
  • Miville-Deschenes M.A.
  • Molinari D.
  • Moneti A.
  • Montier L.
  • Morgante G.
  • Moss A.
  • Narimani A.
  • Natoli P.
  • Oxborrow C.A.
  • Pagano L.
  • Paoletti D.
  • Patanchon G.
  • Patrizii L.
  • Pettorino V.
  • Piacentini F.
  • Polastri L.
  • Polenta G.
  • Puget J.L.
  • Rachen J.P.
  • Racine B.
  • Reinecke M.
  • Remazeilles M.
  • Renzi A.
  • Rossetti M.
  • Roudier G.
  • Rubino-Martin J.A.
  • Ruiz-Granados B.
  • Salvati L.
  • Sandri M.
  • Savelainen M.
  • Scott D.
  • Sirignano C.
  • Sirri G.
  • Stanco L.
  • Suur-Uski A.S.
  • Tauber J.A.
  • Tavagnacco D.
  • Tenti M.
  • Toffolatti L.
  • Tomasi M.
  • Tristram M.
  • Trombetti T.
  • Valiviita J.
  • van Tent F.
  • Vielva P.
  • Villa Francesca
  • Vittorio N.
  • Wandelt B.D.
  • Wehus I.K.
  • White M.
  • Zacchei A.
  • Zonca A.
  Astron.Astrophys., 2017, 607, pp.A95. The six parameters of the standard ΛCDM model have best-fit values derived from the Planck temperature power spectrum that are shifted somewhat from the best-fit values derived from WMAP data. These shifts are driven by features in the Planck temperature power spectrum at angular scales that had never before been measured to cosmic-variance level precision. We have investigated these shifts to determine whether they are within the range of expectation and to understand their origin in the data. Taking our parameter set to be the optical depth of the reionized intergalactic medium τ, the baryon density ωb, the matter density ωm, the angular size of the sound horizon θ∗, the spectral index of the primordial power spectrum, ns, and Ase− 2τ (where As is the amplitude of the primordial power spectrum), we have examined the change in best-fit values between a WMAP-like large angular-scale data set (with multipole moment ℓ < 800 in the Planck temperature power spectrum) and an all angular-scale data set (ℓ < 2500Planck temperature power spectrum), each with a prior on τ of 0.07 ± 0.02. We find that the shifts, in units of the 1σ expected dispersion for each parameter, are { Δτ,ΔAse− 2τ,Δns,Δωm,Δωb,Δθ∗ } = { −1.7,−2.2,1.2,−2.0,1.1,0.9 }, with a χ2 value of 8.0. We find that this χ2 value is exceeded in 15% of our simulated data sets, and that a parameter deviates by more than 2.2σ in 9% of simulated data sets, meaning that the shifts are not unusually large. Comparing ℓ < 800 instead to ℓ> 800, or splitting at a different multipole, yields similar results. We examined the ℓ < 800 model residuals in the ℓ> 800 power spectrum data and find that the features there that drive these shifts are a set of oscillations across a broad range of angular scales. Although they partly appear similar to the effects of enhanced gravitational lensing, the shifts in ΛCDM parameters that arise in response to these features correspond to model spectrum changes that are predominantly due to non-lensing effects; the only exception is τ, which, at fixed Ase− 2τ, affects the ℓ> 800 temperature power spectrum solely through the associated change in As and the impact of that on the lensing potential power spectrum. We also ask, “what is it about the power spectrum at ℓ < 800 that leads to somewhat different best-fit parameters than come from the full ℓ range?” We find that if we discard the data at ℓ < 30, where there is a roughly 2σ downward fluctuation in power relative to the model that best fits the full ℓ range, the ℓ < 800 best-fit parameters shift significantly towards the ℓ < 2500 best-fit parameters. In contrast, including ℓ < 30, this previously noted “low-ℓ deficit” drives ns up and impacts parameters correlated with ns, such as ωm and H0. As expected, the ℓ < 30 data have a much greater impact on the ℓ < 800 best fit than on the ℓ < 2500 best fit. So although the shifts are not very significant, we find that they can be understood through the combined effects of an oscillatory-like set of high-ℓ residuals and the deficit in low-ℓ power, excursions consistent with sample variance that happen to map onto changes in cosmological parameters. Finally, we examine agreement between PlanckTT data and two other CMB data sets, namely the Planck lensing reconstruction and the TT power spectrum measured by the South Pole Telescope, again finding a lack of convincing evidence of any significant deviations in parameters, suggesting that current CMB data sets give an internally consistent picture of the ΛCDM model.Key words: cosmology: observations / cosmic background radiation / cosmological parameters / cosmology: theory (10.1051/0004-6361/201629504)
  DOI : 10.1051/0004-6361/201629504
• Proposal of new solution for service advertisement for ETSI ITS environments: CAM-Infrastructure
  
  • Labiod Houda
  • Servel Alain
  • Segarra Gérard
  • Hammi Badis
  • Monteuuis Jean-Philippe
  , 2017, pp.1-4. Collaborative Intelligent Transportation Systems are almost part of our everyday life. A C-ITS environment can provide numerous services that soon will become essential to roads’ users. The latter resides in improvement of road safety, entertainment, and commercial services. However to provide such services, the C-ITS environment needs an advertisement and dissemination service of the latter. Indeed, users have to be aware of the available services in order to request them if needed. Actual standards of service announcement show their limits, especially regarding the support of several communication profiles. For this reason, this paper, describes a new service advertisement message called CAM-Infrastructure. The latter is compliant with ETSI standards and is deployed in a nationwide scale project.
• Foreword to Radio Science for Humanity: URSI-France 2017 Workshop
  
  • Tanzi Tullio
  • Hamelin Joel
  Radio Science Bulletin, Union Radio-Scientifique Internationale (URSI), 2017 (360), pp.60-61.
• Uniform bootstrap central limit theorems for Harris chains
  
  • Ciolek Gabriela
  , 2017. The main objective of this talk is to present bootstrap uniform functional central limit theorem for Harris recurrent Markov chains over uniformly bounded classes of functions. We show that the result can be generalized also to the unbounded case. To avoid some complicated mixing conditions, we make use of the well-known regeneration properties of Markov chains. We show that in the atomic case the proof of the bootstrap uniform central limit theorem for Markov chains for functions dominated by a function in L2 space proposed by Radulovic (2004) can be significantly simplified. Regenerative properties of Markov chains can be applied in order to extend some concepts in robust statistics from i.i.d. to a Markovian setting. Bertail and Clémençon (2006) have dened an inuence function and Fréchet dierentiability on the torus what allowed to The main objective of this talk is to present bootstrap uniform functional central limit theorem for Harris recurrent Markov chains over uniformly bounded classes of functions. We show that the result can be generalized also to the unbounded case. To avoid some complicated mixing conditions, we make use of the well-known regeneration properties of Markov chains. We show that in the atomic case the proof of the bootstrap uniform central limit theorem for Markov chains for functions dominated by a function in L2 space proposed by Radulovic (2004) can be signicantly simplified. Regenerative properties of Markov chains can be applied in order to extend some concepts in robust statistics from i.i.d. to a Markovian setting. Bertail and Clémençon (2006) have defined an inluence function and Fréchet differentiability on the torus what allowed to extend the notion of robustness from single observations to the blocks of data instead. In this talk, we present bootstrap uniform central limit theorems for Fréchet differentiable functionals in a Markovian case.The notion of robustness from single observations to the blocks of data instead. In this talk, we present bootstrap uniform central limit theorems for Fréchet differentiable functionals in a Markovian case.
• Prioritized network coding scheme for multi-layer video streaming
  
  • Baccouch Hana
  • Ageneau Paul-Louis
  • Tizon Nicolas
  • Boukhatem Nadia
  , 2017.
• Urban area change detection based on generalized likelihood ratio test
  
  • Zhao Weiying
  • Lobry Sylvain
  • Maître Henri
  • Nicolas Jean-Marie
  • Tupin Florence
  , 2017.
• Frame rate vs Resolution: a subjective evaluation of spatio-temporal perceived quality under varying computational budgets
  
  • Debattista Kurt
  • Bugeja Keith
  • Spina Sandro
  • Bashford-Rogers Thomas
  • Hulusic Vedad
  Computer Graphics Forum, Wiley, 2017. Maximising performance for rendered content requires making compromises on quality parameters depending on the computational resources available. Yet, it is currently unclear which parameters best maximise perceived quality. This work investigates perceived quality across computational budgets for the primary spatio-temporal parameters of resolution and frame rate. Three experiments are conducted. Experiment 1 (n = 26) shows that participants prefer fixed frame rates of 60 frames per second (fps) at lower resolutions over 30 fps at higher resolutions. Experiment 2 (n = 24) explores the relationship further with more budgets and quality settings and again finds 60 fps is generally preferred even when more resources are available. Experiment 3 (n = 25) permits the use of adaptive frame rates, and analyses the resource allocation across seven budgets. Results show that while participants allocate more resources to frame rate at lower budgets the situation reverses once higher budgets are available and a frame rate of around 40 fps is achieved. In the overall, the results demonstrate a complex relationship between frame rate and resolution’s effects on perceived quality. This relationship can be harnessed, via the results and models presented, to obtain more cost-effective virtual experiences.
• Semi-automatic teeth segmentation in cone-beam computed tomography by graph-cut with statistical shape prior
  
  • Evain Timothée
  • Ripoche Xavier
  • Atif J.
  • Bloch Isabelle
  , 2017, pp.1197-1200. We propose a new semi-automatic framework for tooth segmentation in Cone-Beam Computed Tomography (CBCT) combining shape priors based on a statistical shape model and graph cut optimization. Poor image quality and similarity between tooth and cortical bone intensities are overcome by strong constraints on the shape and on the targeted area. The segmentation quality was assessed on 64 tooth images for which a reference segmentation was available, with an overall Dice coefficient above 0.95 and a global consistency error less than 0.005.
• Hyperparameter optimization of deep neural networks: combining Hperband with Bayesian model selection
  
  • Bertrand Hadrien
  • Ardon Roberto
  • Perrot Matthieu
  • Bloch Isabelle
  , 2017. One common problem in building deep learning architectures is the choice of the hyper-parameters. Among the various existing strategies, we propose to combine two complementary ones. On the one hand, the Hyperband method formalizes hyper-parameter optimization as a resource allocation problem, where the resource is the time to be distributed between many configurations to test. On the other hand, Bayesian optimization tries to model the hyper-parameter space as efficiently as possible to select the next model to train. Our approach is to model the space with a Gaussian process and sample the next group of models to evaluate with Hyperband. Preliminary results show a slight improvement over each method individually, suggesting the need and interest for further experiments.
• Towards building 3D individual models from MRI segmentation and tractography to enhance surgical planning for pediatric pelvic tumors and malformations
  
  • Muller Cécile
  • Virzi Alessio
  • Marret Jean-Baptiste
  • Mille Eva
  • Berteloot Laureline
  • Grevent David
  • Blanc Thomas
  • Garcelon Nicolas
  • Buffet Isabelle
  • Hullier-Ammard Elisabeth
  • Gori Pietro
  • Boddaert Nathalie
  • Bloch Isabelle
  • Sarnacki Sabine
  , 2017, pp.113-115.
• CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration
  
  • Deledalle Charles-Alban
  • Papadakis Nicolas
  • Salmon Joseph
  • Vaiter Samuel
  SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2017, 10 (1), pp.243-284. In this paper, we propose a new framework to remove parts of the systematic errors affecting popular restoration algorithms, with a special focus for image processing tasks. Generalizing ideas that emerged for $\ell_1$ regularization, we develop an approach re-fitting the results of standard methods towards the input data. Total variation regularizations and non-local means are special cases of interest. We identify important covariant information that should be preserved by the re-fitting method, and emphasize the importance of preserving the Jacobian (w.r.t. the observed signal) of the original estimator. Then, we provide an approach that has a ``twicing'' flavor and allows re-fitting the restored signal by adding back a local affine transformation of the residual term. We illustrate the benefits of our method on numerical simulations for image restoration tasks. (10.1137/16M1080318)
  DOI : 10.1137/16M1080318
• Rate Allocation in Predictive Video Coding Using a Convex Optimization Framework
  
  • Fiengo Aniello
  • Chierchia Giovanni
  • Cagnazzo Marco
  • Pesquet-Popescu Béatrice
  IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2017, 26 (1), pp.479 - 489. Optimal rate allocation is among the most challenging tasks to perform in the context of predictive video coding, because of the dependencies between frames induced by motion compensation. In this paper, using a recursive rate-distortion model that explicitly takes into account these dependencies, we approach the frame-level rate allocation as a convex optimization problem. This technique is integrated into the recent HEVC encoder, and tested on several standard sequences. Experiments indicate that the proposed rate allocation ensures a better performance (in the rate-distortion sense) than the standard HEVC rate control, and with a little loss w.r.t. an optimal exhaustive research which is largely compensated by a much shorter execution time. (10.1109/TIP.2016.2621666)
  DOI : 10.1109/TIP.2016.2621666
• Closed-form expressions of the eigen decomposition of 2 x 2 and 3 x 3 Hermitian matrices
  
  • Deledalle Charles-Alban
  • Denis Loic
  • Tabti Sonia
  • Tupin Florence
  , 2017. The eigen decomposition of covariance matrices is at the core of many data analysis techniques. The study of 2-components or 3-components vector fields typically requires computing numerous eigen decompositions of 2 x 2 or 3 x 3 matrices. This is, for example, the case in the analysis of interferometric or polarimetric SAR images, see MuLoG algorithm (https://hal.archives-ouvertes.fr/hal-01388858). The closed-form expression of eigen-values and eigenvectors then provides a way to derive faster data processing algorithms. This note gives these expressions in the general case (special cases where some coefficients are zero, or the eigenvalues are not separated may not be covered and then require either to introduce a small perturbation of the initial matrix or to derive other expressions).
• Top-k Querying of Unknown Values under Order Constraints (Extended Version)
  
  • Amarilli Antoine
  • Amsterdamer Yael
  • Milo Tova
  • Senellart Pierre
  , 2017. Many practical scenarios make it necessary to evaluate top-k queries over data items with partially unknown values. This paper considers a setting where the values are taken from a numerical domain, and where some partial order constraints are given over known and unknown values: under these constraints, we assume that all possible worlds are equally likely. Our work is the first to propose a principled scheme to derive the value distributions and expected values of unknown items in this setting, with the goal of computing estimated top-k results by interpolating the unknown values from the known ones. We study the complexity of this general task, and show tight complexity bounds, proving that the problem is intractable, but can be tractably approximated. We then consider the case of tree-shaped partial orders, where we show a constructive PTIME solution. We also compare our problem setting to other top-k definitions on uncertain data.