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ugmented 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.
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
[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

Version du 21 novembre 2022 à 14:38


Méthode de travail et objectifs

Affectations sujets

Here is a shared table that present sthe 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 d'étude 2022-2023

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.

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.


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

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

Résumé du sujet

Sujet sur les Réseaux génératifs

  • Enseignant : Pierre De Loor
  • Sujet en lien avec un stage : non
  • description en cours de rédaction

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