Publications

2017

• Non-Local Patch-Based Image Inpainting
  
  • Newson Alasdair
  • Almansa Andrés
  • Gousseau Yann
  • Pérez Patrick
  Image Processing On Line, IPOL - Image Processing on Line, 2017, 7, pp.373-385. Image inpainting is the process of filling in missing regions in an image in a plausible way. In this contribution, we propose and describe an implementation of a patch-based image inpainting algorithm. The method is actually a two-dimensional version of our video inpainting algorithm proposed in [A. Newson et al., Video inpainting of complex scenes, SIAM Journal of Imaging Sciences, 7 (2014)]. The algorithm attempts to minimize a highly non-convex functional, first introducted by Wexler et al. in [Wexler et al., Space-time video completion, CCVPR (2004)]. The functional specifies that a good solution to the inpainting problem should be an image where each patch is very similar to its nearest neighbor in the unoccluded area. Iterations are performed in a multi-scale framework which yields globally coherent results. In this manner two of the major goals of image inpainting, the correct reconstruction of textures and structures, are addressed. We address a series of important practical issues which arise when using such an approach. In particular, we reduce execution times by using the PatchMatch [C. Barnes, PatchMatch: a randomized correspondence algorithm for structural image editing, ACM Transactions on Graphics, (2009)] algorithm for nearest neighbor searches, and we propose a modified patch distance which improves the comparison of textured patches. We address the crucial issue of initialization and the choice of the number of pyramid levels, two points which are rarely discussed in such approaches. We provide several examples which illustrate the advantages of our algorithm, and compare our results with those of state-of-the-art methods. (10.5201/ipol.2017.189)
  DOI : 10.5201/ipol.2017.189
• How to Find the Best Rated Items on a Likert Scale and How Many Ratings Are Enough
  
  • Liu Qing
  • Basu Debabrota
  • Goel Shruti
  • Abdessalem Talel
  • Bressan Stéphane
  , 2017, pp.351-359. (10.1007/978-3-319-64471-4_28)
  DOI : 10.1007/978-3-319-64471-4_28
• A Multilingual System for Cyberbullying Detection: Arabic Content Detection using Machine Learning
  
  • Haidar Batoul
  • Chamoun Maroun
  • Serhrouchni Ahmed
  Advances in Science, Technology and Engineering Systems Journal, Advances in Science Technology and Engineering Systems Journal (ASTESJ), 2017, 2 (6), pp.275-284. (10.25046/aj020634)
  DOI : 10.25046/aj020634
• Similarity and Contrast on Conceptual Spaces for Pertinent Description Generation
  
  • Sileno Giovanni
  • Bloch Isabelle
  • Atif Jamal
  • Dessalles Jean-Louis
  , 2017, LNAI 10505, pp.262-275. Within the general objective of conceiving a cognitive architecture for image interpretation able to generate outputs relevant to several target user profiles, the paper elaborates on a set of operations that should be provided by a cognitive space to guarantee the generation of relevant descriptions. First, it attempts to define a working definition of contrast operation. Then, revisiting well-known results in cognitive studies, it sketches a definition of similarity based on contrast, distin- guished from the metric defined on the conceptual space.
• On the uncontended complexity of anonymous agreement
  
  • Capdevielle Claire
  • Johnen Colette
  • Kuznetsov Petr
  • Milani Alessia
  Distributed Computing, 2017, 30 (6), pp.459-468. (10.1007/s00446-017-0297-z)
  DOI : 10.1007/s00446-017-0297-z
• Non-interference and local correctness in transactional memory
  
  • Kuznetsov Petr
  • Peri Sathya
  Theor. Comput. Sci., 2017, 688, pp.103-116. (10.1016/j.tcs.2016.06.021)
  DOI : 10.1016/j.tcs.2016.06.021
• Discovery and Registration: Finding and Integrating Components into Dynamic Systems
  
  • Rodriguez Berha Helena
  • Moissinac Jean-Claude Jc
  , 2017, pp.325-349. One of the major gaps in the current HTML5 web platform is the lack of an interoperable means for a multimodal application to discover services and applications available in a given space and network, for example, in a smart house with a network of connected objects. To address this gap, the Multimodal Interaction Working Group has produced a draft specification based on distributed services, which aims to support the Discovery and Registration of multimodal components. In this approach, the components are described and virtualized in a Resources Manager communicating bidirectionally through dedicated events. To facilitate the fine-grained management of concurrent multimodal interactions, the Resources Manager registers the distributed components and provides to the Interaction Manager the means to control them. In this way, interoperable search, discovery, and selection of heterogeneous and dynamic features on the Web of Things can be performed by multimodal applications producing natural interaction and a semantically rich user experience. (10.1007/978-3-319-42816-1_15)
  DOI : 10.1007/978-3-319-42816-1_15
• The notion of self-aware computing
  
  • Kounev Samuel
  • Lewis Peter
  • Bellman Kirstie
  • Bencomo Nelly
  • Camara Javier
  • Diaconescu Ada
  • Esterle Lukas
  • Geihs Kurt
  • Giese Holger
  • Gotz Sebastian
  • Inverardi Paola
  • Kephart Jeff
  • Zisman Andrea
  , 2017, pp.3-16.
• Brain lesion detection in 3D PET images using max-trees and a new spatial context criterion
  
  • Urien Hélène
  • Buvat Irène
  • Rougon N. F.
  • Soussan Michael
  • Bloch Isabelle
  , 2017, LNCS 10225, pp.455-466. In this work, we propose a new criterion based on spatial context to select relevant nodes in a max-tree representation of an image, dedicated to the detection of 3D brain tumors for \textsuperscript{18}$F$-FDG PET images. This criterion prevents the detected lesions from merging with surrounding physiological radiotracer uptake. A complete detection method based on this criterion is proposed, and was evaluated on five patients with brain metastases and tuberculosis, and quantitatively assessed using the true positive rates and positive predictive values. The experimental results show that the method detects all the lesions in the PET.
• Détection et segmentation de tumeurs cérébrales en imagerie hybride TEP-IRM
  
  • Urien Hélène
  • Buvat Irène
  • Rougon N. F.
  • Soussan Michael
  • Bloch Isabelle
  , 2017, pp.50.
• Bravo monsieur Le Monde !
  
  • Zayana Karim
  Bulletion de l'APMEP, 2017. Mesurer la circonférence terrestre sans tourner en rond : Ce texte reprend un exposé donné le 10 mars 2017 au lycée Jean Zay à Paris, dans le cadre du plan national de formation « Construction des croisements didactiques en mathématiques et physique-chimie au collège
• A Minimax Optimal Algorithm for Crowdsourcing
  
  • Bonald Thomas
  • Combes Richard
  , 2017. We consider the problem of accurately estimating the reliability of workers based on noisy labels they provide, which is a fundamental question in crowdsourcing. We propose a novel lower bound on the minimax estimation error which applies to any estimation procedure. We further propose Triangular Estimation (TE), an algorithm for estimating the reliability of workers. TE has low complexity, may be implemented in a streaming setting when labels are provided by workers in real time, and does not rely on an iterative procedure. We prove that TE is minimax optimal and matches our lower bound. We conclude by assessing the performance of TE and other state-of-the-art algorithms on both synthetic and real-world data.
• 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.
• 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.
• 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
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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