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== Instructions ==
== Méthode de travail et objectifs ==


Voici quelques indications pour la rédaction de l'étude bibliographique et  sa restitution orale : [https://www.enib.fr/~chevaill/documents/master/siia_bibl_instructions-etude-bibliographique.pdf  instructions biblio].
=== Affectations sujets ===


== Sujets d'étude 2018-2019 ==
Here is a shared table that presents the different subjects of study: [https://lite.framacalc.org/9qt3-siia-bibl_sujets_etude_biblio_2021 list of studies].


=== B18-01 : Les différentes plateformes de simulation à base d'agents et les grands nombres d'agents ===
Students are invited to indicate their choice(s) in this table.


Enseignant référent : Jérémy Rivière
=== Indications générales ===
Voici quelques indications pour la rédaction de l'étude bibliographique et sa restitution orale : [[Media:Siia-bibl_instructions_etude_biblio_2020.pdf|instructions biblio]] (révision nov. 2020).


Il s'agit de recenser les principales plateformes / logiciels permettant de faire de la simulation à base d'agents, en les comparant notamment selon le langage de programmation utilisé et leur capacité à simuler un grand nombre d'agents.
=== Documents à étudier ===


Références :
Comme toute technique d'ingénierie, ou toute démarche scientifique, la réalisation d'une étude bibliographique, appelée aussi revue de littérature (littérature review), doit être réalisée de manière méthodique et apporter des éléments pour en apprécier la justesse et la pertinence. Même si les motivations pour réaliser un tel exercice peuvent être diverses, dans ses grandes lignes, la méthodologie reste la même.  
* Alban Rousset, Bénédicte Herrmann, Christophe Lang. Étude comparative des plateformes parallèles pour systèmes multi-agents. Pascal Felber and Laurent Philippe and Etienne Riviere and Arnaud Tisserand. ComPAS 2014: conférence en parallélisme, architecture et systèmes, Neuchâtel, Suisse. 2014.


* Nikolai, C.; G. Madey (2008). "Tools of the Trade: A Survey of Various Agent Based Modeling Platforms", Journal of Artificial Societies and Social Simulation, 12 (2). Au.  
Voici quelques documents à lire avant et pendant la réalisation de votre étude.


* R.J. Allan (2009) Survey of Agent Based Modelling and Simulation Tools
* [https://www.enib.fr/~chevaill/documents/master/siia_bibl/Systematic_literature_reviews.pdf Guidelines for performing Systematic Literature Reviews in Software Engineering],  Barbara Kitchenham, Stuart Charters, Tech. Report, Keele University and Durham University, 2007.
*  [https://www.enib.fr/~chevaill/documents/master/siia_bibl/Kotsiantis_i07.pdf Supervised Machine Learning: A Review of Classification Techniques], S.K. Kotsiantis, Informatica 31, 2007.
*  [https://www.enib.fr/~chevaill/documents/master/siia_bibl/Wen_etal_ist12.pdf Systematic literature review of machine learning based software development effort estimation models], Wen ''et al.'', Information and Software Technology, 54, 2012.
*  [https://www.enib.fr/~chevaill/documents/master/siia_bibl/Safety_and_Usability_of_Speech_Interfaces_for_In-V.pdf Safety and Usability of Speech Interfaces for In-Vehicle Tasks while Driving: A Brief Literature Review], Adriana Barón and Paul Green, Tec/. Report, The University of Michigan Transportation Research Institute, 2006.


=== B18-02 : Modèles et simulations à base d'agents de butinage chez l'abeille ===
== Sujets libres (sans lien avec un stage ou lié à un stage non attribué) ==


Enseignant référent : Jérémy Rivière
=== How telepresence systems can support collaborative dynamics in large interactive spaces? ===
* Enseignant : [mailto:cedric.fleury@imt-atlantique.fr Cédric Fleury]
* Sujet en lien avec un stage : non.


De nombreux modèles à base d'agents se sont concentré sur l'activité de butinage chez l'abeille. Il vous est demandé dans ce travail d'identifier ces travaux et leurs points communs / différences, notamment sur le contenu des modèles et leurs objectifs, en présentant également leurs avantages et leurs inconvénients.  
Videoconferencing and telepresence have long been a way to enhance communication among remote users. They improve turn-taking, mutual understanding, and negotiation of common ground by supporting non-verbal cues such as eye-gaze direction, facial expressions, gestures, and body langue [3, 6, 10]. They are also an effective solution to avoid the "Uncanny Valley" effect [7] that can be encountered when using avatars.


Références :
However, such systems are often limited to basic setups in which each user must seat in front of a computer equipped with a camera. Other systems, such as Multiview [9] or MMSpace [8], handle groups, but still only group-to-group conversations are possible. This leads to awkward situations in which colleagues in the same building stay in their office to attend a videoconference meeting instead of attending together, or participants are forced to have side conversations via chat. More recent work investigates dynamic setups that allow users to move into the system and interact with share content. t-Rooms [5] displays remote users on circular screens around a tabletop. CamRay [1] handles video communication between two users interacting on remote wall-sized displays. GazeLens [4] integrates a remote user in a group collaboration around physical artifacts on a table. Nevertheless, such systems do not support different moments in the collaboration, such as tightly coupled and loose collaboration, subgroup collaboration, spontaneous or side discussions. Supporting such dynamics in collaboration is a major challenge for the next telepresence systems.
* Jérémy Rivière, Cédric Alaux, Yves Le Conte, Yves Layec, André Lozac'H, Vincent Rodin, Frank Singhoff. Toward a Complete Agent-Based Model of a Honeybee Colony. Highlights of Practical Applications of Agents,  
Multi-Agent Systems, and Complexity: The PAAMS Collection, Jun 2018, Toledo, Spain.


* Dornhaus, A., Klügl, F., Oechslein, C., Puppe, F., Chittka, L.: Benefits of recruitment in honey bees: effects of ecology and colony size in an individual-based model. Behav. Ecol. 17(3), 336–344 (2006)
[1]  I. Avellino, C. Fleury, W. Mackay and M. Beaudouin-Lafon. “CamRay: Camera Arrays Support Remote Collaboration on Wall-Sized Displays”. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI’17). 2017.


* Seeley, T.D., Camazine, S., Sneyd, J.: Collective decision-making in honey bees: how colonies choose among nectar sources. Behav. Ecol. Sociobiol. 28(4), 277–290 (1991)
[3]  E. A. Isaacs and J. C. Tang. “What Video Can and Can’t Do for Collaboration: A Case Study.” Proceedings of the ACM International Conference on Multimedia (MULTIMEDIA’93). 1993.


* de Vries, H., Biesmeijer, J.C.: Modelling collective foraging by means of individual behaviour rules in honey-bees. Behav. Ecol. Sociobiol. 44(2), 109–124 (1998)
[4]  K.-D. Le, I. Avellino, C. Fleury, M. Fjeld, A. Kunz. “GazeLens: Guiding Attention to Improve Gaze Interpretation in Hub-Satellite Collaboration”. Proceedings of the Conference on Human- Computer Interaction (INTERACT’19). 2019.


* Becher, M.A., Grimm, V., et al.: BEEHAVE: a systems model of honeybee colony dynamics and foraging to explore multifactorial causes of colony failure. J. Appl. Ecol. 51(2), 470–482 (2014)
[5]  P. K. Luff, N. Yamashita, H. Kuzuoka, and C. Heath. “Flexible Ecologies And Incongruent Locations.” Proceedings of the Conf. on Human Factors in Computing Systems. (CHI ’15). 1995.


=== B18-03 La place de l'humain (interactions et visualisation) dans les simulations à base d'agents ===
[6]  A. F. Monk and C. Gale. “A Look Is Worth a Thousand Words: Full Gaze Awareness in Video- Mediated Conversation.” In: Discourse Processes 33.3, 2002, pp. 257–278.


Enseignant référent : Jérémy Rivière
[7]  M. Mori, K. F. MacDorman and N. Kageki, “The Uncanny Valley [From the Field]”, IEEE Robotics & Automation Magazine, vol. 19, no. 2, pp. 98-100, 2012.


Les simulations à base d'agents peuvent être utilisée par des non-experts en informatique, par exemple à des fins d'apprentissage, qui ont besoin de moyens d'interactions et de visualisation intuitifs et efficaces avec la simulation. Ce travail demande de recenser les différents moyens utilisés dans le domaine des simulations à base d'agents, et de regrouper les travaux selon ces moyens.
[8]  K. Otsuka, “MMSpace: Kinetically-augmented telepresence for small group-to-group conversations”. Proceedings of 2016 IEEE Virtual Reality (VR’16). 2016.


Références :
[9]  A. Sellen, B. Buxton, and J. Arnott. “Using Spatial Cues to Improve Videoconferencing.” Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI ’92). 1992.
* G. Desmeulles, F. Harrouet, D. Thuault, V. Huchet, P. Redou, L. Gaubert, G. Longelin Péron, P. Ballet and V. Rodin. 3D individual based model for simultaneous growth and interaction of L. Monocytogenes and lactic acid bacteria. ICPMF9, 9th International Conference on Predictive Modelling in Food, pages 11-12, Rio de Janeiro (Brazil), 8-12 September 2015.  


* G. Desmeulles, G. Querrec, P. Redou, S. Kerdélo, L. Misery, V. Rodin and J. Tisseau. The virtual reality applied to the biology understanding: the in virtuo experimentation. Expert Systems with Applications, Elsevier, 30(1):82-92, January 2006.  
[10]  E. S. Veinott, J. Olson, G. M. Olson, and X. Fu. “Video Helps Remote Work: Speakers Who Need to Negotiate Common Ground Benefit from Seeing Each Other.” Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’99). 1999.


* Julie Dugdale, Nargès Bellamine-Ben Saoud, Bernard Pavard, Nico Pallamin. Simulation and Emergency Management. Van de Walle, B. and Turoff, M. and Hiltz,  S. R. Information Systems for Emergency Management, 16, M.E. Sharpe, 2010, Advances in Management Information Systems, 978-0-7656-2134-4.
=== How to represent the physical space surrounding users in remote AR collaboration? ===
* Enseignants : [mailto:cedric.fleury@imt-atlantique.fr Cédric Fleury] et [mailto:thierry.duval@imt-atlantique.fr Thierry Duval]
* Sujet en lien avec un stage : oui ([[Stages|Hybrid Collaborative across Heterogeneous Devices]])
* '''stage non attribué'''


* Lauren Thévin, Fabien Badeig, Julie Dugdale, Olivier Boissier, Catherine Garbay. Un Système Multi-Agent normatif hybride pour l’interaction mixte : application à la gestion de crises. Revue des Sciences et Technologies de l'Information -  Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2015, Dernières avancées en intelligence artificielle, 29 (3-4), pp.453-482.
Augmented Reality (AR) is becoming a very popular technology to support remote collaboration, as it enables users to share virtual content with distant collaborators. However, sharing the physical spaces surrounding users is still a major challenge. Each user involved in an AR collaborative situation enters the shared environment with a part of its own environment [4, 9]. For example, this space can be shared in several ways for two remote users [3]: (i) in an equitable mode (i.e., half from user 1 and half from user 2) [5], (ii) in a host-guest situation where the host imposes the shape of the augmented environment to the guest [7, 8], or (iii) in a mixed environment specifically designed for the collaborative task [6]. Whatever the configuration, the question of how users perceive and use this shared environment arises [2]


=== B18-04 : Les solutions de réalité augmentée sur dispositif Android ===
[1] H. H. Clark, and S. E. Brennan. "Grounding in communication". In: L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 127–149). American Psychological Association. 1991.


Enseignant référent : Thierry Duval
[2] S. R. Fussell, R. E. Kraut, and J. Siegel. “Coordination of communication: effects of shared visual context on collaborative work”. Proceedings of the 2000 ACM conference on Computer supported cooperative work (CSCW '00). 2000.


Il s'agit de réaliser un état de l'art sur les outils logiciels permettant de faire de la Réalité Augmentée sur dispositif Android (type téléphone ou tablette). L'étude consiste à un tableau comparatif décrivant les avantages et inconvénients des différentes solutions existantes, les environnements de développement associés, les langages de programmation qu'il faut utiliser pour manipuler ces API.
[3] B. T. Kumaravel, F. Anderson, G. Fitzmaurice, B. Hartmann, and Tovi Grossman. "Loki:Facilitating Remote Instruction of Physical Tasks Using Bi-Directional Mixed-Reality Telepresence". Proceedings of the ACM Symposium on User Interface Software and Technology (UIST '19), 2019.
Idéalement il faudrait également avoir testé chacun de ces produits (pour les produits payants, seulement si il y a une licence gratuite...) et évalué la difficulté de déploiement.


Références :
[4] P. Ladwig and C. Geiger. “A Literature Review on Collaboration in Mixed Reality”. International Conference on Remote Engineering and Virtual Instrumentation (REV). 2018.
* https://www.wikitude.com/store/


* https://deepar.ai/augmented-reality-sdk/
[5] N. H. Lehment, D. Merget and G. Rigoll. "Creating automatically aligned consensus realities for AR videoconferencing". IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2014.


* https://www.easyar.com/
[6] T. Mahmood, W. Fulmer, N. Mungoli, J. Huang and A. Lu. "Improving Information Sharing and Collaborative Analysis for Remote GeoSpatial Visualization Using Mixed Reality". IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2019.


* http://www.artoolkitx.org/
[7] O. Oda, C. Elvezio, M. Sukan, S. Feiner, and B. Tversky. "Virtual Replicas for Remote Assistance in Virtual and Augmented Reality". Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology (UIST '15), 2015.


* https://developer.vuforia.com/
[8] S. Orts-Escolano, C. Rhemann, S. Fanello, W. Chang, A. Kowdle, Y. Degtyarev, and al. “Holoportation: Virtual 3D Teleportation in Real-time”. Proceedings of the 29th Annual Symposium on User Interface Software and Technology (UIST '16). 2016.


* https://nyatla.jp/nyartoolkit/wp/
[9] M. Sereno, X. Wang, L. Besancon, M. J. Mcguffin and T. Isenberg, "Collaborative Work in Augmented Reality: A Survey". IEEE Transactions on Visualization and Computer Graphics. 2020.


=== B18-05 : Synthèse vocale à l'aide de réseaux de neurones ===
=== Principes et mise en oeuvre des architectures de Machine Learning de type « Transformers » ===
* Enseignant :  [mailto:pierre.deloor@enib.fr Pierre De Loor]
* Sujet en lien avec un stage : non.


Enseignant référent : Pierre Chevaillier
[[Media:BIBL-2021_Deloor_SujetBiblioTransformer.pdf| Résumé du sujet]]


L'objectif est d'étudier les avancées récentes dans le domaine de la synthèse vocale par l'utilisation de réseaux de neurones de type deep-learning. Ces solutions visent à améliorer la prosodie des phrases énoncées par de telles systèmes de façon à la rendre plus naturelle. Il s'agit de comparer les méthodes utilisées  dans les systèmes récents.  
=== Sujet sur les réseaux adversiaux génératifs (GAN) ===
* Enseignant :  [mailto:pierre.deloor@enib.fr Pierre De Loor]
* Sujet en lien avec un stage : non


Références :
[[Media:Generative_Adversial_Networks_2022.pdf| Résumé du sujet]]


* Fan, Y., Qian, Y., Xie, F.-L., & Soong, F. K. (2014.). TTS Synthesis with Bidirectional LSTM Based Recurrent Neural Networks, In Proceedings of Interspeech'14, pp. 1964-1968
=== Modèle du comportement réactif du regard pour un agent virtuel inoccupé, basé sur signaux visuels et acoustiques ===
* Enseignants : [mailto:elisabetta.bevacqua@enib.fr Elisabetta Bevacqua] et [mailto:desmeulles@enib.fr Gireg Desmeulles]
* Sujet en lien avec un stage : oui ([[Stages]])
* '''stage non attribué'''


* Okamoto, T., Tachibana, K., Toda, T., Shiga, Y., & Kawai, H. (2018). Deep neural network-based power spectrum reconstruction to improve quality of vocoded speech with limited acoustic parameters. Acoustical Science and Technology, 39(2), 163–166.
=== Informatique affective : myographie et réalité virtuelle  ===
* Enseignants : [mailto:augereau@enib.fr Olivier Augereau]
* Sujet en lien avec un stage : oui ([[Stages]])
* '''stage non attribué'''


* Wan, V., Agiomyrgiannakis, Y., Silen, H., & Vít, J. (2017). Google’s Next-Generation Real-Time Unit-Selection Synthesizer Using Sequence-to-Sequence LSTM-Based Autoencoders. In Proceedings of Interspeech 2017, pp. 1143–1147.
=== Exploitation de données de League of Legends pour l'étude de la complexité dans les décisions humaines ===
* Enseignants : [mailto:augereau@enib.fr Olivier Augereau]
* Sujet en lien avec un stage : oui ([[Stages]])
* '''stage non attribué'''


* Wu, Z., Watts, O., & King, S. (2016). Merlin: An Open Source Neural Network Speech Synthesis System. 9th ISCA Speech Synthesis Workshop,  202–207.
===  Comment simuler de façon efficace et réaliste les essaims de robots ? ===
* Enseignant : [mailto:jeremy.riviere@univ-brest.fr Jérémy Rivière]
* Sujet en lien avec un stage : non.


* Zen, H., & Sak, H. (2015). Unidirectional long short-term memory recurrent neural network with recurrent output layer for low-latency speech synthesis. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). South Brisbane, Queensland, Australia, pp. 4470–4474.
L'étude des "Robot swarms", ou essaims de robots, porte sur les systèmes comprenant de nombreux robots - ou drones - volants, roulants, etc. qui se coordonnent de façon autonome, à partir de règles de contrôle locales basées sur les perceptions du robot et son état actuel. La conception du comportement de ces robots passent le plus souvent par un outil de simulation. Cette étude bibliographique s'intéresse aux plateformes de simulation existantes d'essaims de robots. L'objectif est de proposer le recensement le plus exhaustif possible de ces plateformes, d'en faire une synthèse, et de les catégoriser selon des critères à définir : efficacité, réalisme, langage de programmation, licence, portabilité, etc.


==== B18-06 : Simulateurs de systèmes multi-cellulaires ====
[1] Yihan Zhang, Lyon Zhang, Hanlin Wang, Fabián E. Bustamante, and Michael Rubenstein. 2020. SwarmTalk - Towards Benchmark Software Suites for Swarm Robotics Platforms. In Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS '20). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 1638–1646.


Enseignant référent : Pascal Ballet
[2] Schranz, M., Umlauft, M., Sende, M., & Elmenreich, W. (2020). Swarm Robotic Behaviors and Current Applications. Frontiers in robotics and AI, 7, 36. https://doi.org/10.3389/frobt.2020.00036


* PhysiCell : https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005991
[3] Webots


* BioCellion : https://academic.oup.com/bioinformatics/article/30/21/3101/2422245
Mots-clés : Multi-robot System, Swarm Robotic, Simulation Platform, Robot Simulator


* CompuCell 3D : http://www.compucell3d.org/
===  Comment simuler de façon efficace et réaliste les systèmes multicellulaires ? ===
* Enseignant : [mailto:pascal.ballet@univ-brest.fr Pascal Ballet]
* Sujet en lien avec un stage : non.


* SimCells : http://virtulab.univ-brest.fr/simcells.html
Cette étude bibliographique s'intéresse aux plateformes de simulation existantes de cellules vivantes par l'approche multiagent ou assimilées (modèle cellulaire de Potts, automates cellulaire). L'objectif est de proposer le recensement le plus exhaustif possible de ces plateformes, d'en faire une synthèse, et de les catégoriser selon des critères à définir : efficacité, réalisme, langage de programmation, licence, portabilité, etc.


==== B18-07 : Interaction Humain-Système : reconnaissance d'activités humaines en environnement naturel ====
[1] Seunghwa Kang, Simon Kahan, Jason McDermott, Nicholas Flann, Ilya Shmulevich, Biocellion : accelerating computer simulation of multicellular biological system models , Bioinformatics, Volume 30, Issue 21, 1 November 2014, Pages 3101–3108, https://doi.org/10.1093/bioinformatics/btu498


Enseignant référent : Alexis Nédélec
[2] Starruß, J., De Back, W., Brusch, L., & Deutsch, A. (2014). Morpheus: a user-friendly modeling environment for multiscale and multicellular systems biology. Bioinformatics, 30(9), 1331-1332.


Le sujet proposé consiste à faire une étude bibliographique sur les algorithmes d'apprentissage machine dédiés à la reconnaissance de gestes et d'activités humaines par un système informatique pour établir une interaction entre un humain et un humanoïde de synthèse dans un environnement naturel.
[3] Morpheus, https://morpheus.gitlab.io/
Cette étude portera plus spécifiquement sur la détection et la reconnaissance d'activités humaines à partir de squelette 3D [2, 4] dans des flux vidéos [1,3,5].


[1] Dushyant et. al. "VNECT: Real-time 3d human pose estimation with a single RGB camera". ACM Transactions on Graphics (SIGGRAPH 2017), Los Angeles, USA, 2017.
[4] Swat, M. H., Thomas, G. L., Belmonte, J. M., Shirinifard, A., Hmeljak, D., & Glazier, J. A. (2012). Multi-scale modeling of tissues using CompuCell3D. In Methods in cell biology (Vol. 110, pp. 325-366). Academic Press.
[2] Ke et. al. "a new representation of skeleton sequences for 3d action recognition". Computer Vision and Pattern Recognition 2017, 2017.
 
[3] Wang et. al. "rgb-d-based human motion recognition with deep learning : A survey". Elsevier Computer Vision and Image Understanding (CVIU), 2018.
[5] Ballet, P. (2018). SimCells, an advanced software for multicellular modeling Application to tumoral and blood vessel co-development.
[4] Tae Soo Kim and Austin Reiter. "interpretable 3d human action analysis with temporal convolutional networks". Computer Vision and Pattern Recognition 2017, 2017.
 
[5] Wu, Sharma, and Blumenstein. "recent advances in video-based human action recognition using deep learning : A review". International Joint Conference on Neural Networks (IJCNN), 2017.
[6] Centillyon, https://centyllion.com/fr/
 
Mots clés : Cellular Potts Model, Multi-agent, Multi-cellular simulator.
 
=== IA pour la traduction automatique de l'humour et des jeux de mots ===
* Enseignant :  [mailto:bosser@enib.fr Anne-Gwenn Bosser]
* Sujet en lien avec un stage : non
 
[[Media:JOKER_-_Sujets_bibliographie_2022-23.pdf| Résumé du sujet]]
 
== Sujets inclus dans les stages affectés ==
 
=== Techniques for localized data representation in Augmented Reality ===
* Enseignants : [mailto:etienne.peillard@imt-atlantique.fr Etienne Peillard] et [mailto:Aymeric.Henard@univ-brest.fr Aymeric Henard]
* Sujet en lien avec un stage : oui ([[Stages|Visualisation immersive et localisée de données en Réalité Augmentée]])
* '''stage attribué'''
 
Augmented reality allows for the superimposition of virtual elements in a real-world environment that can be associated with it. It enables, for example, the display of temperature data in a room to visually identify cold spots, or the display of robot speed and trajectory to understand their movement. However, the display possibilities are twofold: the data to be displayed can be of various types (discrete/continuous, 1D/2D/3D/see 4D), and there are numerous ways to display them. Furthermore, due to augmented reality's limitations, some techniques may not be adapted or may cause display issues, particularly when the visualizations become distant or overlapping. This research topic aims to review all of the techniques that allow data to be displayed in AR in a co-localized manner, identifying their benefits and drawbacks as detailed in the scientific literature.
 
[1] Olshannikova, Ekaterina ; Ometov, Aleksandr ; Koucheryavy, Yevgeni ; Olsson, Thomas: Visualizing Big Data with augmented and virtual reality: challenges and research agenda. In: Journal of Big Data Bd. 2, SpringerOpen (2015), Nr. 1, S. 1–27
 
[2] Hedley, Nicholas R. ; Billinghurst, Mark ; Postner, Lori ; May, Richard ; Kato, Hirokazu: Explorations in the use of augmented reality for geographic visualization. In: Presence: Teleoperators and Virtual Environments Bd. 11 (2002), Nr. 2, S. 119–133
 
[3] Olshannikova, Ekaterina ; Ometov, Aleksandr ; Koucheryavy, Yevgeni: Towards big data visualization for augmented reality. In: Proceedings - 16th IEEE Conference on Business Informatics, CBI 2014 Bd. 2, Institute of Electrical and Electronics Engineers Inc. (2014), S. 33–37 — ISBN 9781479957781
 
[4] Miranda, Brunelli P. ; Queiroz, Vinicius F. ; Araújo, Tiago D.O. ; Santos, Carlos G.R. ; Meiguins, Bianchi S.: A low-cost multi-user augmented reality application for data visualization. In: Multimedia Tools and Applications Bd. 81, Springer (2022), Nr. 11, S. 14773–14801
 
[5] Martins, Nuno Cid ; Marques, Bernardo ; Alves, João ; Araújo, Tiago ; Dias, Paulo ; Santos, Beatriz Sousa: Augmented reality situated visualization in decision-making. In: Multimedia Tools and Applications Bd. 81, Springer (2022), Nr. 11, S. 14749–14772
 
=== How collaboration in mixed reality can benefit from the use of heterogeneous devices? ===
 
* Enseignants : [mailto:cedric.fleury@imt-atlantique.fr Cédric Fleury] et [mailto:etienne.peillard@imt-atlantique.fr Etienne Peillard]
* Sujet en lien avec un stage : oui ([[Stages|Perception of Shared Spaces in Collaborative Augmented Reality]])
* '''stage attribué'''
 
The massive development of display technologies brings a wide range of new devices, such as mobile phones, AR/VR headsets and large displays, available to the general public. These devices offer many opportunities for co-located and remote collaboration on physical and digital content. Some can handle groups of co-located users [10, 13], while others enable remote users to connect in various situations [3, 6, 11, 14]. For example, some previous systems allow users to use a mobile device to interact with a co-located partner wearing a VR headset [4, 7]. Other systems enable users in VR to guide a remote collaborator using an AR headset [1, 8, 9, 12].
[1] H. Bai, P. Sasikumar, J. Yang, and M. Billinghurst. "A User Study on Mixed Reality Remote
Collaboration with Eye Gaze and Hand Gesture Sharing". Proceedings of the CHI Conference on
Human Factors in Computing Systems (CHI’20), 2020.
 
[2] H. H. Clark, and S. E. Brennan. "Grounding in communication". In: L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 127–149). American Psychological Association. 1991.
 
[3] C. Fleury, T. Duval, V. Gouranton, A. Steed. "Evaluation of Remote Collaborative Manipulation for Scientific Data Analysis", ACM Symposium on Virtual Reality Software and Technology (VRST’12), 2012.
 
[4] J. Gugenheimer, E. Stemasov, J. Frommel, and E. Rukzio. "ShareVR: Enabling Co-Located Experiences for Virtual Reality between HMD and Non-HMD Users". Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 2017.
 
[5] J. Hollan and S. Stornetta. "Beyond being there". In : Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI’92), 1992.
 
[6] B. T. Kumaravel, F. Anderson, G. Fitzmaurice, B. Hartmann, and Tovi Grossman. "Loki:Facilitating Remote Instruction of Physical Tasks Using Bi-Directional Mixed-Reality Telepresence". Proceedings of the ACM Symposium on User Interface Software and Technology (UIST '19), 2019.
 
[7] B. T. Kumaravel, C. Nguyen, S. DiVerdi, and B. Hartmann. "TransceiVR: Bridging Asymmetrical Communication Between VR Users and External Collaborators". Proceedings of the ACM Symposium on User Interface Software and Technology (UIST '20), 2020.
 
[8] M. Le Chénéchal, T. Duval, J. Royan, V. Gouranton, and B. Arnaldi. “Vishnu: Virtual Immersive Support for HelpiNg Users - An Interaction Paradigm for Remote Collaborative Maintenance in Mixed Reality”. Proceedings of 3DCVE 2016 (IEEE VR 2016 International Workshop on 3D Collaborative Virtual Environments). 2016.
 
[9] M. Le Chénéchal, T. Duval, V. Gouranton, J. Royan, and B. Arnaldi. “The Stretchable Arms for Collaborative Remote Guiding”. Proceedings of ICAT-EGVE 2015, Eurographics. 2015.
 
[10] C. Liu, O. Chapuis, M. Beaudouin-Lafon, and E. Lecolinet. “Shared Interaction on a Wall-Sized Display in a Data Manipulation Task.” In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. CHI ’16.
 
[11] P. Mohr, S. Mori, T. Langlotz, B. H. Thomas, D. Schmalstieg, and D. Kalkofen. "Mixed Reality Light Fields for Interactive Remote Assistance". Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’20), 2020.
 
[12] O. Oda, C. Elvezio, M. Sukan, S. Feiner, and B. Tversky. "Virtual Replicas for Remote Assistance in Virtual and Augmented Reality". Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology (UIST '15), 2015.
 
[13] Y. Okuya, O. Gladin, N. Ladévèze, C. Fleury, P. Bourdot. "Investigating Collaborative Exploration of Design Alternatives on a Wall-Sized Display", ACM Conference on Human Factors in Computing Systems (CHI’20), 2020.
 
[14] H. Xia, S. Herscher, K. Perlin, and D. Wigdor. "Spacetime: Enabling Fluid Individual and Collaborative Editing in Virtual Reality". Proceedings of the ACM Symposium on User Interface Software and Technology (UIST ’18), 2018.

Dernière version du 28 novembre 2022 à 09:54


Méthode de travail et objectifs

Affectations sujets

Here is a shared table that presents the different subjects of study: list of studies.

Students are invited to indicate their choice(s) in this table.

Indications générales

Voici quelques indications pour la rédaction de l'étude bibliographique et sa restitution orale : instructions biblio (révision nov. 2020).

Documents à étudier

Comme toute technique d'ingénierie, ou toute démarche scientifique, la réalisation d'une étude bibliographique, appelée aussi revue de littérature (littérature review), doit être réalisée de manière méthodique et apporter des éléments pour en apprécier la justesse et la pertinence. Même si les motivations pour réaliser un tel exercice peuvent être diverses, dans ses grandes lignes, la méthodologie reste la même.

Voici quelques documents à lire avant et pendant la réalisation de votre étude.

Sujets libres (sans lien avec un stage ou lié à un stage non attribué)

How telepresence systems can support collaborative dynamics in large interactive spaces?

Videoconferencing and telepresence have long been a way to enhance communication among remote users. They improve turn-taking, mutual understanding, and negotiation of common ground by supporting non-verbal cues such as eye-gaze direction, facial expressions, gestures, and body langue [3, 6, 10]. They are also an effective solution to avoid the "Uncanny Valley" effect [7] that can be encountered when using avatars.

However, such systems are often limited to basic setups in which each user must seat in front of a computer equipped with a camera. Other systems, such as Multiview [9] or MMSpace [8], handle groups, but still only group-to-group conversations are possible. This leads to awkward situations in which colleagues in the same building stay in their office to attend a videoconference meeting instead of attending together, or participants are forced to have side conversations via chat. More recent work investigates dynamic setups that allow users to move into the system and interact with share content. t-Rooms [5] displays remote users on circular screens around a tabletop. CamRay [1] handles video communication between two users interacting on remote wall-sized displays. GazeLens [4] integrates a remote user in a group collaboration around physical artifacts on a table. Nevertheless, such systems do not support different moments in the collaboration, such as tightly coupled and loose collaboration, subgroup collaboration, spontaneous or side discussions. Supporting such dynamics in collaboration is a major challenge for the next telepresence systems.

[1] I. Avellino, C. Fleury, W. Mackay and M. Beaudouin-Lafon. “CamRay: Camera Arrays Support Remote Collaboration on Wall-Sized Displays”. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI’17). 2017.

[3] E. A. Isaacs and J. C. Tang. “What Video Can and Can’t Do for Collaboration: A Case Study.” Proceedings of the ACM International Conference on Multimedia (MULTIMEDIA’93). 1993.

[4] K.-D. Le, I. Avellino, C. Fleury, M. Fjeld, A. Kunz. “GazeLens: Guiding Attention to Improve Gaze Interpretation in Hub-Satellite Collaboration”. Proceedings of the Conference on Human- Computer Interaction (INTERACT’19). 2019.

[5] P. K. Luff, N. Yamashita, H. Kuzuoka, and C. Heath. “Flexible Ecologies And Incongruent Locations.” Proceedings of the Conf. on Human Factors in Computing Systems. (CHI ’15). 1995.

[6] A. F. Monk and C. Gale. “A Look Is Worth a Thousand Words: Full Gaze Awareness in Video- Mediated Conversation.” In: Discourse Processes 33.3, 2002, pp. 257–278.

[7] M. Mori, K. F. MacDorman and N. Kageki, “The Uncanny Valley [From the Field]”, IEEE Robotics & Automation Magazine, vol. 19, no. 2, pp. 98-100, 2012.

[8] K. Otsuka, “MMSpace: Kinetically-augmented telepresence for small group-to-group conversations”. Proceedings of 2016 IEEE Virtual Reality (VR’16). 2016.

[9] A. Sellen, B. Buxton, and J. Arnott. “Using Spatial Cues to Improve Videoconferencing.” Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI ’92). 1992.

[10] E. S. Veinott, J. Olson, G. M. Olson, and X. Fu. “Video Helps Remote Work: Speakers Who Need to Negotiate Common Ground Benefit from Seeing Each Other.” Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’99). 1999.

How to represent the physical space surrounding users in remote AR collaboration?

Augmented Reality (AR) is becoming a very popular technology to support remote collaboration, as it enables users to share virtual content with distant collaborators. However, sharing the physical spaces surrounding users is still a major challenge. Each user involved in an AR collaborative situation enters the shared environment with a part of its own environment [4, 9]. For example, this space can be shared in several ways for two remote users [3]: (i) in an equitable mode (i.e., half from user 1 and half from user 2) [5], (ii) in a host-guest situation where the host imposes the shape of the augmented environment to the guest [7, 8], or (iii) in a mixed environment specifically designed for the collaborative task [6]. Whatever the configuration, the question of how users perceive and use this shared environment arises [2]

[1] H. H. Clark, and S. E. Brennan. "Grounding in communication". In: L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 127–149). American Psychological Association. 1991.

[2] S. R. Fussell, R. E. Kraut, and J. Siegel. “Coordination of communication: effects of shared visual context on collaborative work”. Proceedings of the 2000 ACM conference on Computer supported cooperative work (CSCW '00). 2000.

[3] B. T. Kumaravel, F. Anderson, G. Fitzmaurice, B. Hartmann, and Tovi Grossman. "Loki:Facilitating Remote Instruction of Physical Tasks Using Bi-Directional Mixed-Reality Telepresence". Proceedings of the ACM Symposium on User Interface Software and Technology (UIST '19), 2019.

[4] P. Ladwig and C. Geiger. “A Literature Review on Collaboration in Mixed Reality”. International Conference on Remote Engineering and Virtual Instrumentation (REV). 2018.

[5] N. H. Lehment, D. Merget and G. Rigoll. "Creating automatically aligned consensus realities for AR videoconferencing". IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2014.

[6] T. Mahmood, W. Fulmer, N. Mungoli, J. Huang and A. Lu. "Improving Information Sharing and Collaborative Analysis for Remote GeoSpatial Visualization Using Mixed Reality". IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2019.

[7] O. Oda, C. Elvezio, M. Sukan, S. Feiner, and B. Tversky. "Virtual Replicas for Remote Assistance in Virtual and Augmented Reality". Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology (UIST '15), 2015.

[8] S. Orts-Escolano, C. Rhemann, S. Fanello, W. Chang, A. Kowdle, Y. Degtyarev, and al. “Holoportation: Virtual 3D Teleportation in Real-time”. Proceedings of the 29th Annual Symposium on User Interface Software and Technology (UIST '16). 2016.

[9] M. Sereno, X. Wang, L. Besancon, M. J. Mcguffin and T. Isenberg, "Collaborative Work in Augmented Reality: A Survey". IEEE Transactions on Visualization and Computer Graphics. 2020.

Principes et mise en oeuvre des architectures de Machine Learning de type « Transformers »

Résumé du sujet

Sujet sur les réseaux adversiaux génératifs (GAN)

Résumé du sujet

Modèle du comportement réactif du regard pour un agent virtuel inoccupé, basé sur signaux visuels et acoustiques

Informatique affective : myographie et réalité virtuelle

Exploitation de données de League of Legends pour l'étude de la complexité dans les décisions humaines

Comment simuler de façon efficace et réaliste les essaims de robots ?

L'étude des "Robot swarms", ou essaims de robots, porte sur les systèmes comprenant de nombreux robots - ou drones - volants, roulants, etc. qui se coordonnent de façon autonome, à partir de règles de contrôle locales basées sur les perceptions du robot et son état actuel. La conception du comportement de ces robots passent le plus souvent par un outil de simulation. Cette étude bibliographique s'intéresse aux plateformes de simulation existantes d'essaims de robots. L'objectif est de proposer le recensement le plus exhaustif possible de ces plateformes, d'en faire une synthèse, et de les catégoriser selon des critères à définir : efficacité, réalisme, langage de programmation, licence, portabilité, etc.

[1] Yihan Zhang, Lyon Zhang, Hanlin Wang, Fabián E. Bustamante, and Michael Rubenstein. 2020. SwarmTalk - Towards Benchmark Software Suites for Swarm Robotics Platforms. In Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS '20). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 1638–1646.

[2] Schranz, M., Umlauft, M., Sende, M., & Elmenreich, W. (2020). Swarm Robotic Behaviors and Current Applications. Frontiers in robotics and AI, 7, 36. https://doi.org/10.3389/frobt.2020.00036

[3] Webots

Mots-clés : Multi-robot System, Swarm Robotic, Simulation Platform, Robot Simulator

Comment simuler de façon efficace et réaliste les systèmes multicellulaires ?

Cette étude bibliographique s'intéresse aux plateformes de simulation existantes de cellules vivantes par l'approche multiagent ou assimilées (modèle cellulaire de Potts, automates cellulaire). L'objectif est de proposer le recensement le plus exhaustif possible de ces plateformes, d'en faire une synthèse, et de les catégoriser selon des critères à définir : efficacité, réalisme, langage de programmation, licence, portabilité, etc.

[1] Seunghwa Kang, Simon Kahan, Jason McDermott, Nicholas Flann, Ilya Shmulevich, Biocellion : accelerating computer simulation of multicellular biological system models , Bioinformatics, Volume 30, Issue 21, 1 November 2014, Pages 3101–3108, https://doi.org/10.1093/bioinformatics/btu498

[2] Starruß, J., De Back, W., Brusch, L., & Deutsch, A. (2014). Morpheus: a user-friendly modeling environment for multiscale and multicellular systems biology. Bioinformatics, 30(9), 1331-1332.

[3] Morpheus, https://morpheus.gitlab.io/

[4] Swat, M. H., Thomas, G. L., Belmonte, J. M., Shirinifard, A., Hmeljak, D., & Glazier, J. A. (2012). Multi-scale modeling of tissues using CompuCell3D. In Methods in cell biology (Vol. 110, pp. 325-366). Academic Press.

[5] Ballet, P. (2018). SimCells, an advanced software for multicellular modeling Application to tumoral and blood vessel co-development.

[6] Centillyon, https://centyllion.com/fr/

Mots clés : Cellular Potts Model, Multi-agent, Multi-cellular simulator.

IA pour la traduction automatique de l'humour et des jeux de mots

Résumé du sujet

Sujets inclus dans les stages affectés

Techniques for localized data representation in Augmented Reality

Augmented reality allows for the superimposition of virtual elements in a real-world environment that can be associated with it. It enables, for example, the display of temperature data in a room to visually identify cold spots, or the display of robot speed and trajectory to understand their movement. However, the display possibilities are twofold: the data to be displayed can be of various types (discrete/continuous, 1D/2D/3D/see 4D), and there are numerous ways to display them. Furthermore, due to augmented reality's limitations, some techniques may not be adapted or may cause display issues, particularly when the visualizations become distant or overlapping. This research topic aims to review all of the techniques that allow data to be displayed in AR in a co-localized manner, identifying their benefits and drawbacks as detailed in the scientific literature.

[1] Olshannikova, Ekaterina ; Ometov, Aleksandr ; Koucheryavy, Yevgeni ; Olsson, Thomas: Visualizing Big Data with augmented and virtual reality: challenges and research agenda. In: Journal of Big Data Bd. 2, SpringerOpen (2015), Nr. 1, S. 1–27

[2] Hedley, Nicholas R. ; Billinghurst, Mark ; Postner, Lori ; May, Richard ; Kato, Hirokazu: Explorations in the use of augmented reality for geographic visualization. In: Presence: Teleoperators and Virtual Environments Bd. 11 (2002), Nr. 2, S. 119–133

[3] Olshannikova, Ekaterina ; Ometov, Aleksandr ; Koucheryavy, Yevgeni: Towards big data visualization for augmented reality. In: Proceedings - 16th IEEE Conference on Business Informatics, CBI 2014 Bd. 2, Institute of Electrical and Electronics Engineers Inc. (2014), S. 33–37 — ISBN 9781479957781

[4] Miranda, Brunelli P. ; Queiroz, Vinicius F. ; Araújo, Tiago D.O. ; Santos, Carlos G.R. ; Meiguins, Bianchi S.: A low-cost multi-user augmented reality application for data visualization. In: Multimedia Tools and Applications Bd. 81, Springer (2022), Nr. 11, S. 14773–14801

[5] Martins, Nuno Cid ; Marques, Bernardo ; Alves, João ; Araújo, Tiago ; Dias, Paulo ; Santos, Beatriz Sousa: Augmented reality situated visualization in decision-making. In: Multimedia Tools and Applications Bd. 81, Springer (2022), Nr. 11, S. 14749–14772

How collaboration in mixed reality can benefit from the use of heterogeneous devices?

The massive development of display technologies brings a wide range of new devices, such as mobile phones, AR/VR headsets and large displays, available to the general public. These devices offer many opportunities for co-located and remote collaboration on physical and digital content. Some can handle groups of co-located users [10, 13], while others enable remote users to connect in various situations [3, 6, 11, 14]. For example, some previous systems allow users to use a mobile device to interact with a co-located partner wearing a VR headset [4, 7]. Other systems enable users in VR to guide a remote collaborator using an AR headset [1, 8, 9, 12]. [1] H. Bai, P. Sasikumar, J. Yang, and M. Billinghurst. "A User Study on Mixed Reality Remote Collaboration with Eye Gaze and Hand Gesture Sharing". Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’20), 2020.

[2] H. H. Clark, and S. E. Brennan. "Grounding in communication". In: L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 127–149). American Psychological Association. 1991.

[3] C. Fleury, T. Duval, V. Gouranton, A. Steed. "Evaluation of Remote Collaborative Manipulation for Scientific Data Analysis", ACM Symposium on Virtual Reality Software and Technology (VRST’12), 2012.

[4] J. Gugenheimer, E. Stemasov, J. Frommel, and E. Rukzio. "ShareVR: Enabling Co-Located Experiences for Virtual Reality between HMD and Non-HMD Users". Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 2017.

[5] J. Hollan and S. Stornetta. "Beyond being there". In : Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI’92), 1992.

[6] B. T. Kumaravel, F. Anderson, G. Fitzmaurice, B. Hartmann, and Tovi Grossman. "Loki:Facilitating Remote Instruction of Physical Tasks Using Bi-Directional Mixed-Reality Telepresence". Proceedings of the ACM Symposium on User Interface Software and Technology (UIST '19), 2019.

[7] B. T. Kumaravel, C. Nguyen, S. DiVerdi, and B. Hartmann. "TransceiVR: Bridging Asymmetrical Communication Between VR Users and External Collaborators". Proceedings of the ACM Symposium on User Interface Software and Technology (UIST '20), 2020.

[8] M. Le Chénéchal, T. Duval, J. Royan, V. Gouranton, and B. Arnaldi. “Vishnu: Virtual Immersive Support for HelpiNg Users - An Interaction Paradigm for Remote Collaborative Maintenance in Mixed Reality”. Proceedings of 3DCVE 2016 (IEEE VR 2016 International Workshop on 3D Collaborative Virtual Environments). 2016.

[9] M. Le Chénéchal, T. Duval, V. Gouranton, J. Royan, and B. Arnaldi. “The Stretchable Arms for Collaborative Remote Guiding”. Proceedings of ICAT-EGVE 2015, Eurographics. 2015.

[10] C. Liu, O. Chapuis, M. Beaudouin-Lafon, and E. Lecolinet. “Shared Interaction on a Wall-Sized Display in a Data Manipulation Task.” In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. CHI ’16.

[11] P. Mohr, S. Mori, T. Langlotz, B. H. Thomas, D. Schmalstieg, and D. Kalkofen. "Mixed Reality Light Fields for Interactive Remote Assistance". Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’20), 2020.

[12] O. Oda, C. Elvezio, M. Sukan, S. Feiner, and B. Tversky. "Virtual Replicas for Remote Assistance in Virtual and Augmented Reality". Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology (UIST '15), 2015.

[13] Y. Okuya, O. Gladin, N. Ladévèze, C. Fleury, P. Bourdot. "Investigating Collaborative Exploration of Design Alternatives on a Wall-Sized Display", ACM Conference on Human Factors in Computing Systems (CHI’20), 2020.

[14] H. Xia, S. Herscher, K. Perlin, and D. Wigdor. "Spacetime: Enabling Fluid Individual and Collaborative Editing in Virtual Reality". Proceedings of the ACM Symposium on User Interface Software and Technology (UIST ’18), 2018.

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