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=== Affectations sujets ===
=== Affectations sujets ===


Here is a shared table that present the different subject of study: [[Framacalc|https://lite.framacalc.org/9qt3-siia-bibl_sujets_etude_biblio_2021]]
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].


 
Students are invited to indicate their choice(s) in this table.
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{| class="wikitable"
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! Etudiant.e !! Sujet  !! encadrant.e.s
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| ABGRALL Théo || Modèle pour la génération du comportement d’un groupe d’élèves virtuels en présence d’un enseignant réel || Elisabetta Bevacqua et Pierre de Loor
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| ALVES BUENO Matheus || Fédération de modèles pour des approches multi-points de vues || Joël Champeau
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| AUGER François || Modèles de soutien à l’autonomie des apprenants (sans stage) || Jean-Marie Gilliot
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| BENDOU Nassim || Les différentes plateformes de simulation à base d'agents et les grands nombres d'agents || Jérémy Rivière
|-
|DANIEL Tristan || Les solutions de réalité augmentée sur dispositif Android || Thierry Duval
|-
| DELANOE Mael || Variantes Narratives pour l’Entraînement aux habiletés sociales (sans stage) || Anne Gwenn Bosser et Nathalie Le Bigot
|-
| FAVERO PEREIRA Paulo Henrique || Synthèse vocale à l'aide de réseaux de neurones || Pierre Chevaillier
|-
| KADEM Sonia || Simulateurs de systèmes multi-cellulaires || Pascal ballet
|-
| LATIBI Adel || Anticipation d'activités utilisateur pour les interfaces plastique (couplé avec stage) || Pierre De Loor - Éric Maisel
|-
|MOREIRA FREITAS Helon || Interaction Humain-Système : reconnaissance d'activités humaines en environnement naturel (sans stage) || Alexis Nédélec
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| NGADI Hamza || Génération et coarticulation de gestes pour un agent virtuel (couplé avec stage) || Gireg Desmeulles - Elisabetta Bevacqua
|-
| ROYET Mikael || Sujet à définir / stage : Modèles de dialogue pour l'interrogation de bases de données || P. Chevaillier
|-
| SEBBAR Elias || Visualisation immersive et interactions avec les simulations à base d'agents || Jérémy Rivière
|-
| TAZTAZ Ibitssem || Modèles et simulations à base d'agents de butinage chez l'abeille || Jérémy Rivière
|}
 
-->


=== Indications générales ===
=== Indications générales ===
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*  [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.
*  [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.


== Sujets d'étude 2021-2022 ==
== 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? ===
* Enseignant : [mailto:cedric.fleury@imt-atlantique.fr Cédric Fleury]
* Sujet en lien avec un stage : non.
 
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.


=== Programmation de systèmes domotiques par les utilisateurs finaux ===
[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 : Eric Maisel (maisel@enib.fr), Lab-STICC, ENIB
[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? ===
* 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'''
 
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 » ===
* Enseignant :  [mailto:pierre.deloor@enib.fr Pierre De Loor]
* Sujet en lien avec un stage : non.
* Sujet en lien avec un stage : non.


Le développement de la programmation événementielle, basée sur des règles trigger-action, contribue au développement des systèmes domotiques en permettant la mise en relation entre capteurs (de température, de luminosité, de présence, ...) et effecteurs (ampoules, radiateurs, stores, ...). L'utilisation de ces systèmes ayant pour objectif d'améliorer la sécurité et le confort dans les bâtiments mais également de permettre d'en réduire l'emprunte écologique. La personnalisation de ces systèmes est nécessaire de façon à les adapter aux différents contextes tant architecturaux que technologiques, environnementaux et culturels. A court et moyen terme cette adaptation passe encore par une programmation de ces systèmes domotiques par les utilisateurs finaux (tout un chacun chez soi, le personnel soignant voire les patients dans les hôpitaux, les salariés dans les bureaux, ...). Cette tâche de programmation est plus complexe qu'il n'y parait et suppose le développement d'assistants logiciels de façon à la rendre accessible.
[[Media:BIBL-2021_Deloor_SujetBiblioTransformer.pdf| Résumé du sujet]]


L'objet de cette étude bibliographique est d'une part de présenter en quoi consiste cette programmation trigger-action à partir d'articles académiques et d'autre part d'esquisser un panorama des différentes approches envisageables afin  d'en faciliter l'utilisation par les utilisateurs finaux.
=== Sujet sur les réseaux adversiaux génératifs (GAN) ===
* Enseignant :  [mailto:pierre.deloor@enib.fr Pierre De Loor]
* Sujet en lien avec un stage : non


B. Ur, E. McManus, M. Pak Yong Ho, M. L. Littman, "Practical trigger-action programming in the smart home", Proc. of the SIGCHI Conference on Human Factors in Computing Systems, pp 802-812, CHI'14, Avril 2014, Toronto, Canada.
[[Media:Generative_Adversial_Networks_2022.pdf| Résumé du sujet]]


B. Ur, M. Pak Yong Ho, S. Brawner, J. Lee, S. Menniken, N. Picard, D. Schulze, M. L. Littman, "Trigger-Action Programming in the Wild : An Analysis of 200.000 IFTTT Recipes" in Proc. of the 2016 CHI Conference on Human Factors in Computing Systems, pp-3227-3231, CHI'16, Mai 2016, San Jose, USA.
=== 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'''


J. Huang, M. Cakmak, "Supporting mental model accuracy in trigger-action programming" in Proc. of the 2015 ACM International Conference on Pervasive and Ubiquitous Computing, pp 215-225, UbiComp'15, Septembre 2015,Osaka, Japon.
=== Informatique affective : myographie et réalité virtuelle  ===
* Enseignants : [mailto:augereau@enib.fr Olivier Augereau]
* Sujet en lien avec un stage : oui ([[Stages]])
* '''stage non attribué'''


F. Paterno, S. Alawadi, "Towards Intelligent Personalization of IoT Platforms" in Proc. of 2019 ACM Conference on Intelligent User Interfaces, IUI'19, Mars 2019, Los Angeles, USA.
=== 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'''


A. Mattioli, F. Paterno, "A Visual Environment for End-User Creation of IoT Customization Rule with Recommendation Support" in Proc. of the International Conference on Advanced Visual Interfaces, pp 1-5, AVI'20, Septembre 2020, Salerno, Italie.
===  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.


F. Corno, L. De Russis, A. Monge Roffarello, "TAPrec : Supporting the Composition of Trigger-Action Rules Through Dynamic Recommendations" in Proc. of the 25th Conference on Intelligent User Interfaces, pp 579-588, IUI'20, Mars 2020, Cagliari, Itale.
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.


F. Corno, L. De Russis, A. Monge Roffarello, "A Semantic Web Approach to Simplifying Trigger-Action Programming in the IoT", in Computer, vol 50, Issue 11, pp 18-24, 2017.
[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.


A.-M. Vainio, M. Valtonen, J. Vanhala, "Proactive Fuzzy Control and Adaptation Methods for Smart Homes" in IEEE Intelligent Systems, vol 23 issue 2, pp 42-49, 2008.
[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


A.-M. Vainio, M. Valtonen, J. Vanhala, "Learning and adaptive fuzzy control system for smart home", in Developing Ambient Intelligence, pp 28-47, Springer.
[3] Webots


=== Systèmes de recommandation sérendipitifs ===
Mots-clés : Multi-robot System, Swarm Robotic, Simulation Platform, Robot Simulator


* Enseignant•e•(s) : Eric Maisel (maisel@enib.fr), Lab-STICC, ENIB
===  Comment simuler de façon efficace et réaliste les systèmes multicellulaires ? ===
* sujet en lien avec un stage : non.
* Enseignant : [mailto:pascal.ballet@univ-brest.fr Pascal Ballet]
* Sujet en lien avec un stage : non.
 
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.


Les systèmes de recommandation sont utilisés pour proposer à un utilisateur particulier confronté à un problème donné un ensemble de solutions pertinentes. Ils sont d'autant plus nécessaires que la quantité d'informations accessibles ne cesse d'augmenter et de dépasser la quantité d'information qu'un être humain peut traiter.
[5] Ballet, P. (2018). SimCells, an advanced software for multicellular modeling Application to tumoral and blood vessel co-development.


Il s'agira dans ce travail de se focaliser sur un problème particulier : celui des bulles informationnelles. L'apparition de ces bulles est directement lié à la nature des algorithmes de recommandation : ceux-ci calculent leurs propositions en tenant compte des choix précédents de l'utilisateur ou de ceux des autres utilisateurs dans la mesure où ceux-ci sont similaires à l'utilisateur considéré. Dans les deux cas les recommandations faites à cet utilisateur restent limitées et n'évoluent que peu.
[6] Centillyon, https://centyllion.com/fr/


La sérendipité - une des cibles de cette étude bibliographique - est la propriété que satisfont les systèmes de recherche d'information quand ils sont capables de proposer des solutions qui sont à la fois pertinentes pour l'utilisateur et auxquelles cet utilisateur ne s'attendait pas. Cette propriété est une des solutions aux bulles informationnelles.
Mots clés : Cellular Potts Model, Multi-agent, Multi-cellular simulator.


Cette étude bibliographique a pour objectif d'une part de rappeler ce que sont les systèmes de recommandation, en particulier les systèmes de recommandation basés sur les connaissances et d'autre part de présenter les différentes approches permettant de mettre en oeuvre des systèmes de recommandation sérendipitifs. Il faudra également s'intéresser à la manière dont ces systèmes peuvent être évalués.
=== 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]]


A. Ameen, "Knowledge based Recommendation System in Semantic Web - A Survey" in International Journal of Computer Applications, Vol. 182, No 43, Mars 2019 .
== Sujets inclus dans les stages affectés ==


Y. Du, S. Ranwez, N. Sutton-Charani, V. Ranwez, "Apport des ontologies aux systèmes de recommandation : état de l'art et perspective", In Proc. of 30es Journées Francophones d'Ingéniérie des Connaissances, IC 2019, AFIA, Juillet 2019, Toulouse, France, pp 64-77 .
=== 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'''


Y. Wang, N. Stash, L. Aroyo, L. Hollink, G. Scheiber, "Using Semantic Relations for Content-based Recommender Systems in Cultural heritage", in Proc. of Worshop on Ontology Patterns 2009  in ISWC workshop, 2009.
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.


D. Kotlov, S Wang, J. Veijalaien, "A survey of serendipity in recommender system", Knowledge-based Systems, vol 111, pp 180-192, November 2016 .
[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


D Kotlov, J. Veijalain, S. Wang, "Challenges of Serendipity in Recommender Systems", in Proc. of the 12th International Conference on Web Information Systems and Technologies, WEBIST 2016, Vol 2 pp 251-256 .
[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


N.I.Y. Saat, S.A.M. Noah, M. Mohd, "Towards Serendipity for Content-Based Recommender Systems", International Journal on Advanced Science Engineering Information Technology, Vol. 8, No 4-2, pp 1762-1769, 2018 .
[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


L. Iaquinta, M.de Gemmis, P. Lops, G. Semeraro, M. Filannino, P. Molino, "Introducing Serendipity in a Content-based Recommender System", in Proc. of the IEEE Eighth International Conference on Hybrid Intelligent Systems, Barcelone, Espagne.
[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


E. E. Toms, "Serendipitous Information Retrieval", in Proc. of DELOS, Workshop : Information Seeking, Searching and Quering in Digital Libraries, pp 17-20, 2000 .
[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


L. McGinty, B. Smyth (2003) On the Role of Diversity in Conversational Recommender Systems. In: Ashley K.D., Bridge D.G. (eds) Case-Based Reasoning Research and Development. ICCBR 2003. Lecture Notes in Computer Science, vol 2689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45006-8_23
=== How collaboration in mixed reality can benefit from the use of heterogeneous devices? ===


T. Dorjmaa, T. Shin, "Evaluating the Quality of Recommendation System by Using Serendipity Measure", in Journal of Intelligent Systems, Vol 25, No 4, pp 89-103, Décembre 2019.
* 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'''


M. Kaminskas, D. Bridge, "Measuring Surprise in Recommender Systems", in Proc. of Workshop on Recommender Systems Evaluation : Dimensions and Design (REDD 2014), held in conjunction with RecSys 2014, Octobre 2014, Silicon Valley, USA.
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.


A. S. Nugroho, I. Ardiyanto, T. B. Adji, "User Curiosity Factor in Determining Serendipity of Recommender System", in proc of the International Journal of Innovative Technology and Exploring Engineering IJITEE, Vol 5, No 3, Septembre 2021.
[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.


A. Menk, L. Sebastia, R. Ferreira, "Curumin, A serendipitous Recommender System based on Human Curiosity" in Procedia Computer Science 112 (2017), pp 484-493.  
[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.


X Niu, F. Abbas, M. L. Maher, K. Grace, "Surprise Me If You Can : Serendipity in Health Information", Proc of the 2018 CHI Conference on Human Factors in Computing SystemsCHI 2018, CHI 2018, pp 1-12, Avril 2018, Montréal, Canada.
[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.


=== Étude des techniques de prédiction en Machine Learning pour lutter contre l’échec et le décrochage scolaire ===
[5] J. Hollan and S. Stornetta. "Beyond being there". In : Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI’92), 1992.


* Enseignante : Fahima DJELIL
[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.
* Sujet en lien avec un stage : non.


=== Algorithmes de comportements auto-organisés pour des essaims de drones ===
[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.


=== Interactions avec essaim de drones  ===
[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.


* Enseignant•e•(s) : Jérémy Rivière
[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.
* Lien avec le stage Robotique en essaims et Systèmes Multi-Agents.


Il s'agira dans la bibliographie de faire une veille technologique des différents dispositifs de tracking existants, puis de comparer et d'évaluer ceux qui sont utilisés en particulier dans des travaux de recherche sur les essaims de robots (Mona et autres).
[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.


=== Techniques et usages possibles de la réalité virtuelle pour l’empathie environnementale  ===
[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.
=== Génération automatique d’humour ou de jeux de mots ===
=== Principes et mise en oeuvre des architectures de Machine Learning de type « Transformers » ===


* Enseignant : Pierre De Loor, Lab-STICC, COMMEDIA, ENIB.
[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.


[[Fichier:BIBL-2021 DELoor transformer.pdf|vignette|subject description]]
[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.


=== L'incarnation sensorimotrice d'un agent virtuel chez un humain en RV ===
[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.
=== Self-learning agents having intrinsic motivation to learn ===
=== Can a naive agents learn a representation of space from its sensorimotor experience ===
=== Recommandations de visualisation pour la cybersécurité ===
=== Méthodes de segmentation sémantique de nuages de points  ===
=== Étude de l'impact des techniques d'interaction sur la perception en Réalité Augmentée ===
=== IHM pour l'exploration de données temporelles ===
=== Communication non verbale en environnement virtuel ===
=== Caractérisation Affective Automatique d’une Expérience Immersive ===
=== Digital commensability in VR ===
=== Reconnaissance automatique d’activités humaines ===

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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