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Generative Artificial Intelligence for Immersive Analytics
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0009-0005-4979-6059
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0003-3639-9327
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-9527-4594
2025 (English)In: Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications / [ed] Bashford-Rogers T., Meneveaux D., Ammi M., Ziat M., Jänicke S., Purchase H., Radeva P., Furnari A., Bouatouch K., Sousa A.A., SciTePress, 2025, Vol. 1, p. 938-946Conference paper, Published paper (Refereed)
Abstract [en]

Generative artificial intelligence (GenAI) models have advanced various applications with their ability to generate diverse forms of information, including text, images, audio, video, and 3D models. In visual computing, their primary applications have focused on creating graphic content and enabling data visualization on traditional desktop interfaces, which help automate visual analytics (VA) processes. With the rise of affordable immersive technologies, such as virtual reality (VR), augmented reality (AR), and mixed reality (MR), immersive analytics (IA) has been an emerging field offering unique opportunities for deeper engagement and understanding of complex data in immersive environments (IEs). However, IA system development remains resource-intensive and requires significant expertise, while integrating GenAI capabilities into IA is still under early exploration. Therefore, based on an analysis of recent publications in these fields, this position paper investigates how GenAI can support future IA systems for more effective data exploration with immersive experiences. Specifically, we discuss potential directions and key issues concerning future GenAI-supported IA applications. 

Place, publisher, year, edition, pages
SciTePress, 2025. Vol. 1, p. 938-946
Series
VISIGRAPP, ISSN 2184-5921, E-ISSN 2184-4321
Keywords [en]
Extended Reality, Generative Artificial Intelligence, Immersive Analytics, Visualization
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:bth-27748DOI: 10.5220/0013308400003912Scopus ID: 2-s2.0-105001960708OAI: oai:DiVA.org:bth-27748DiVA, id: diva2:1953493
Conference
20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2025, Porto, Feb 26-28, 2025
Part of project
HINTS - Human-Centered Intelligent Realities
Funder
Knowledge Foundation, 20220068Available from: 2025-04-22 Created: 2025-04-22 Last updated: 2025-04-22Bibliographically approved

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Wang, ChaomingSundstedt, VeronicaGarro, Valeria

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