Publications

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.
• Uniform bootstrap central limit theorems for Harris chains
  
  • Ciołek 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.
• 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.
• 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
• Les facettes de l'Open Data : émergence, fondements et travail en coulisses
  
  • Denis Jérôme
  • Goëta Samuel
  , 2017, pp.121-138. Dans ce chapitre, nous revenons sur l'émergence des politiques d'open data en mettant en lumière les grands principes (de la transparence jusqu'à la modernisation de l'administration, en passant par la libre circulation de l'information) que différentes initiatives ont progressivement stabilisés pour faire de l'ouverture des données publiques un enjeu international. Nous montrons ensuite, à partir d'une enquête ethnographique menée dans plusieurs institutions françaises ce que cette ouverture implique concrètement : un travail délicat qui demeure largement invisible et représente le coût caché des principes fondateurs de l'open data.
• La fabrique des données brutes. Le travail en coulisses de l'open data
  
  • Denis Jérôme
  • Goëta Samuel
  , 2017. Depuis quelques années, les initiatives d’open data se sont multipliées à travers le monde. Présentées jusque dans la presse grand public comme une ressource inexploitée, le « pétrole » sur lequel le monde serait assis, les données publiques sont devenues objet de toutes les attentions et leur ouverture porteuse de toutes les promesses, à la fois terreau d’un renouveau démocratique et moteur d’une innovation distribuée. Comme dans les sciences, qui ont connu un mouvement de focalisation similaire sur les données et leur partage, l’injonction à l’ouverture opère une certaine mise en invisibilité. Le vocabulaire de la « libération », de la « transparence » et plus encore celui de la « donnée brute » efface toute trace des conditions de production des données, des contextes de leurs usages initiaux et pose leur universalité comme une évidence. Ce chapitre explore les coulisses de l’open data afin de retrouver les traces de cette production et d’en comprendre les spécificités. À partir d’une série d’entretiens ethnographiques dans diverses institutions, il décrit la fabrique des données brutes, dont l’ouverture ne se résume jamais à une mise à disponibilité immédiate, évidente et universelle. Il montre que trois aspects sont particulièrement sensibles dans le processus d’ouverture : l’identification, l'extraction et la « brutification » des données. Ces trois séries d’opérations donnent à voir l’épaisseur sociotechnique des données brutes dont la production mêle dimensions organisationnelles, politiques et techniques.
• Trends in Social Network Analysis - Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment
  
  • Missaoui Rokia
  • Abdessalem Talel
  • Latapy Mathieu
  , 2017, pp.255. <p>The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, stochastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.</p> <p> </p> (10.1007/978-3-319-53420-6)
  DOI : 10.1007/978-3-319-53420-6
• 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).
• 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.
• Règles d'Associations Temporelles de signaux sociaux pour la synthèse d'Agents Conversationnels Animés : Application aux attitudes sociales
  
  • Janssoone Thomas
  • Clavel Chloé
  • Bailly Kevin
  • Richard Gael
  Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2017. Afin d'améliorer l'interaction entre des humains et des agents conversationnels animés (ACA), l'un des enjeux majeurs du domaine est de générer des agents crédibles socialement. Dans cet article, nous présentons une méthode, intitulée SMART pour social multimodal association rules with timing, capable de trouver automatiquement des associations temporelles entre l'utilisation de signaux sociaux (mouvements de tête, expressions faciales, prosodie. . .) issues de vidéos d'interactions d'humains exprimant différents états affectifs (comportement, attitude, émotions,. . .). Notre système est basé sur un algorithme de fouille de séquences qui lui permet de trouver des règles d'associations temporelles entre des signaux sociaux extraits automatiquement de flux audio-vidéo. SMART va également analyser le lien de ces règles avec chaque état affectif pour ne conserver que celles qui sont pertinentes. Finalement, SMART va les enrichir afin d'assurer une animation facile d'un ACA pour qu'il exprime l'état voulu. Dans ce papier, nous formalisons donc l'implémentation de SMART et nous justifions son inté-rêt par plusieurs études. Dans un premier temps, nous montrons que les règles calculées sont bien en accord avec la littérature en psychologie et sociologie. Ensuite, nous présentons les résultats d'évaluations perceptives que nous avons conduites suite à des études de corpus pro-posant l'expression d'attitudes sociales marquées. ABSTRACT. In the field of Embodied Conversational Agent (ECA) one of the main challenges is to generate socially believable agents. The long run objective of the present study is to infer rules for the multimodal generation of agents' socio-emotional behaviour. In this paper, we introduce the Social Multimodal Association Rules with Timing (SMART) algorithm. It proposes to Revue d'intelligence artificielle-n o 4/2017, 511-537 512 RIA. Volume 31-n o 4/2017 learn the rules from the analysis of a multimodal corpus composed by audio-video recordings of human-human interactions. The proposed methodology consists in applying a Sequence Mining algorithm using automatically extracted Social Signals such as prosody, head movements and facial muscles activation as an input. This allows us to infer Temporal Association Rules for the behaviour generation. We show that this method can automatically compute Temporal Association Rules coherent with prior results found in the literature especially in the psychology and sociology fields. The results of a perceptive evaluation confirms the ability of a Temporal Association Rules based agent to express a specific stance. (10.3166/RIA.31.511-537)
  DOI : 10.3166/RIA.31.511-537
• 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.
• Nonequilibrium Green's functions theory for the alpha factor of quantum cascade lasers
  
  • Pereira Mauro
  • Winge David
  • Wacker Andreas
  • Jumpertz Louise
  • Michel Florian
  • Pawlus Robert
  • Elsassaer Wolfgang
  • Schires Kevin
  • Carras Mathieu
  • Grillot Frédéric
  , 2017.
• Étude des perturbations des systèmes de positionnement magnéto-inductifs en intérieur, » Journées nationales micorondes
  
  • Gharat Vighnesh
  • Colin Elizabeth
  • Baudoin Geneviève
  • Richard Damien Richard
  , 2017.
• Method, device, and computer program for transmitting portions of encapsulated media content
  
  • Denoual Franck
  • Mazé Frédéric
  • Ruellan Hervé
  • Le Feuvre J.
  • Ouedraogo Nael
  , 2017.
• Cournot-Nash Equilibria for Bandwidth Allocation under Base-Station Cooperation
  
  • Gomez J S
  • Vergne A
  • Martins P
  • Decreusefond Laurent
  • Chen Wei
  , 2017. —In this paper, a novel resource allocation scheme based on discrete Cournot-Nash equilibria and optimal transport theory is proposed. The originality of this framework lies in the joint optimization of downlink bandwidth allocation and cooperation between base stations. A tractable formalization is given in the form of a quadratic optimization problem. A low complexity approximate solution is derived and theoretically characterized. Simulations highlight the existence of an optimal working point, that maximizes user satisfaction ratio and network load. The impact of the network deployment on the optimum is numerically investigated, thanks to the β-Ginibre model. Indeed, base stations are assumed to be drawn according to β-Ginibre point processes. Numerical analysis shows that the network performance increases with β going to one.
• Physical attacks
  
  • El Mrabet Nadia
  • Goubin Louis
  • Fournier Jacques Jean-Alain
  • Jauvart Damien
  • Guilley Sylvain
  • Moreau Martin
  • Rauzy Pablo
  • Rondepierre Franck
  , 2017.
• Large Scale Density-friendly Graph Decomposition via Convex Programming
  
  • Danisch Maximilien
  • Chan T-H. Hubert
  • Sozio Mauro
  , 2017.
• Yet another proof of the entropy power inequality
  
  • Rioul Olivier
  IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2017, 63 (6), pp.3595-3599. Yet another simple proof of the entropy power inequality is given, which avoids both the integration over a path of Gaussian perturbation and the use of Young’s inequality with sharp constant or Rényi entropies. The proof is based on a simple change of variables, is formally identical in one and several dimensions, and easily settles the equality case. (10.1109/TIT.2017.2676093)
  DOI : 10.1109/TIT.2017.2676093
• Optimal two-step prediction in regression
  
  • Chételat Didier
  • Lederer Johannes
  • Salmon Joseph
  Electronic Journal of Statistics, Shaker Heights, OH : Institute of Mathematical Statistics, 2017, 11 (1), pp.2519-2546.
• Planck intermediate results - L. Evidence of spatial variation of the polarized thermal dust spectral energy distribution and implications for CMB B-mode analysis
  
  • Aghanim N.
  • Ashdown M.
  • Aumont J.
  • Baccigalupi C.
  • Ballardini M.
  • Banday A.J.
  • Barreiro R.B.
  • Bartolo N.
  • Basak S.
  • Benabed K.
  • Bernard Jean-Paul
  • Bersanelli M.
  • Bielewicz P.
  • Bonaldi A.
  • Bonavera L.
  • Bond J.R.
  • Borrill J.
  • Bouchet F.R.
  • Boulanger F.
  • Bracco A.
  • Burigana C.
  • Calabrese E.
  • Cardoso J.F.
  • Chiang H.C.
  • Colombo L.P.L.
  • Combet C.
  • Comis B.
  • Crill B.P.
  • Curto A.
  • Cuttaia F.
  • Davis R.J.
  • de Bernardis P.
  • de Rosa A.
  • de Zotti G.
  • Delabrouille J.
  • Delouis J. M.
  • Di Valentino E.
  • Dickinson C.
  • Diego J.M.
  • Dore O.
  • Douspis M.
  • Ducout A.
  • Dupac X.
  • Dusini S.
  • Efstathiou G.
  • Elsner F.
  • Ensslin T.A.
  • Eriksen H.K.
  • Falgarone E.
  • Fantaye Y.
  • Finelli F.
  • Frailis M.
  • Fraisse A.A.
  • Franceschi E.
  • Frolov A.
  • Galeotta S.
  • Galli S.
  • Ganga K.
  • Genova-Santos R.T.
  • Gerbino M.
  • Ghosh T.
  • Giard M.
  • Gonzalez-Nuevo J.
  • Gorski K.M.
  • Gregorio A.
  • Gruppuso A.
  • Gudmundsson J.E.
  • Hansen F.K.
  • Helou G.
  • Herranz D.
  • Hivon E.
  • Huang Z.
  • Jaffe A.H.
  • Jones W.C.
  • Keihanen E.
  • Keskitalo R.
  • Kisner T.S.
  • Krachmalnicoff N.
  • Kunz M.
  • Kurki-Suonio H.
  • Lagache G.
  • Lahteenmaki A.
  • Lamarre J.M.
  • Lasenby A.
  • Lattanzi M.
  • Lawrence C.R.
  • Le Jeune M.
  • Levrier F.
  • Liguori M.
  • Lilje P.B.
  • Lopez-Caniego M.
  • Lubin P.M.
  • 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.
  • Melchiorri A.
  • Mennella A.
  • Migliaccio M.
  • Mitra S.
  • Miville-Deschenes M.A.
  • Molinari D.
  • Moneti A.
  • Montier L.
  • Morgante G.
  • Moss A.
  • Naselsky P.
  • Norgaard-Nielsen H.U.
  • Oxborrow C.A.
  • Pagano L.
  • Paoletti D.
  • Partridge B.
  • Patrizii L.
  • Perdereau O.
  • Perotto L.
  • Pettorino V.
  • Piacentini F.
  • Plaszczynski S.
  • Polenta G.
  • Puget J.L.
  • Rachen J.P.
  • Reinecke M.
  • Remazeilles M.
  • Renzi A.
  • Rocha G.
  • 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.
  • Tenti M.
  • Toffolatti L.
  • Tomasi M.
  • Tristram M.
  • Trombetti T.
  • Valiviita J.
  • Vansyngel F.
  • van Tent F.
  • Vielva P.
  • Wandelt B.D.
  • Wehus I.K.
  • Zacchei A.
  • Zonca A.
  Astronomy & Astrophysics - A&A, EDP Sciences, 2017, 599, pp.A51. The characterization of the Galactic foregrounds has been shown to be the main obstacle in thechallenging quest to detect primordial B-modes in the polarized microwave sky. We make use of the Planck-HFI 2015 data release at high frequencies to place new constraints on the properties of the polarized thermal dust emission at high Galactic latitudes. Here, we specifically study the spatial variability of the dust polarized spectral energy distribution (SED), and its potential impact on the determination of the tensor-to-scalar ratio, r. We use the correlation ratio of the CBBℓ angular power spectra between the 217 and 353 GHz channels as a tracer of these potential variations, computed on different high Galactic latitude regions, ranging from 80% to 20% of the sky. The new insight from Planck data is a departure of the correlation ratio from unity that cannot be attributed to a spurious decorrelation due to the cosmic microwave background, instrumental noise, or instrumental systematics. The effect is marginally detected on each region, but the statistical combination of all the regions gives more than 99% confidence for this variation in polarized dust properties. In addition, we show that the decorrelation increases when there is a decrease in the mean column density of the region of the sky being considered, and we propose a simple power-law empirical model for this dependence, which matches what is seen in the Planck data. We explore the effect that this measured decorrelation has on simulations of the BICEP2-Keck Array/Planck analysis and show that the 2015 constraints from these data still allow a decorrelation between the dust at 150 and 353 GHz that is compatible with our measured value. Finally, using simplified models, we show that either spatial variation of the dust SED or of the dust polarization angle are able to produce decorrelations between 217 and 353 GHz data similar to the values we observe in the data. Key words: cosmic background radiation / cosmology: observations / submillimeter: ISM / dust, extinction⋆ Corresponding author: L. Montier, e-mail: Ludovic.Montier@irap.omp.eu; J. Aumont, e-mail: jonathan.aumont@ias.u-psud.fr (10.1051/0004-6361/201629164)
  DOI : 10.1051/0004-6361/201629164
• Robust dynamic range computation for high dynamic range content
  
  • Hulusic Vedad
  • Valenzise Giuseppe
  • Debattista Kurt
  • Dufaux Frederic
  , 2017. High dynamic range (HDR) imaging has become an important topic in both academic and industrial domains. Nevertheless, the concept of dynamic range (DR), which underpins HDR, and the way it is measured are still not clearly understood. The current approach to measure DR results in a poor correlation with perceptual scores (r ≈ 0.6). In this paper, we analyze the limitations of the existing DR measure, and propose several options to predict more accurately subjective DR judgments. Compared to the traditional DR estimates, the proposed measures show significant improvements in Spearman's and Pearson's correlations with subjective data (up to r ≈ 0.9). Despite their straightforward nature, these improvements are particularly evident in specific cases, where the scores obtained by using the classical measure have the highest error compared to the perceptual mean opinion score.
• Very high resolution and interferometric SAR: Markovian and patch-based non-local mathematical models
  
  • Deledalle Charles-Alban
  • Denis Loïc
  • Ferraioli Giampaolo
  • Pascazio Vito
  • Schirinzi Gilda
  • Tupin Florence
  , 2017. This chapter is dedicated to very high resolution (VHR) SAR imagery, including interferometric applications. First, the principles of SAR data acquisition are presented as well as the different types of configurations. The widely adopted Gaussian complex model of fully developed speckle is described as well as more advanced statistical models for VHR SAR data that account for textures. The following two parts are devoted to SAR image estimation and to image denoising within two different frameworks. First, Markovian modeling is introduced and the associated optimization approaches are presented, including graph-cut based optimization. The second framework is the patch-based non-local modeling of SAR complex data. Both frameworks are adapted to SAR images through the use of statistical models specific to SAR imagery. Their applications to amplitude data, interferometry, and fusion with optical data are illustrated. A special focus is given to phase unwrapping applied to single and multi- channel interferometry, showing the usefulness of local and global contextual models. (10.1007/978-3-319-66330-2)
  DOI : 10.1007/978-3-319-66330-2
• Parallel Combining: Making Use of Free Cycles
  
  • Aksenov Vitaly
  • Kuznetsov Petr
  Computing Research Repository, ACM / ArXiv, 2017, abs/1710.07588.