AHCI RESEARCH GROUP

Publications

Papers published in international journals,
proceedings of conferences, workshops and books.

OUR RESEARCH

Scientific Publications

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2025

Oliveira, E. A. Masasi De; Sousa, R. T.; Bastos, A. A.; Cintra, L. Martins De Freitas; Filho, A. R. G.

Immersive Virtual Museums with Spatially-Aware Retrieval-Augmented Generation Proceedings Article

In: IMX - Proc. ACM Int. Conf. Interact. Media Experiences, pp. 437–440, Association for Computing Machinery, Inc, 2025, ISBN: 979-840071391-0 (ISBN).

Abstract | Links | BibTeX | Tags: Association reactions, Behavioral Research, Generation systems, Geographics, Human computer interaction, Human engineering, Immersive, Information Retrieval, Interactive computer graphics, Language Model, Large language model, large language models, Museums, Retrieval-Augmented Generation, Search engines, Spatially aware, User interfaces, Virtual environments, Virtual museum, Virtual museum., Virtual Reality, Visual Attention, Visual languages

@inproceedings{masasi_de_oliveira_immersive_2025,

title = {Immersive Virtual Museums with Spatially-Aware Retrieval-Augmented Generation},

author = {E. A. Masasi De Oliveira and R. T. Sousa and A. A. Bastos and L. Martins De Freitas Cintra and A. R. G. Filho},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007979183&doi=10.1145%2f3706370.3731643&partnerID=40&md5=db10b41217dd8a0b0705c3fb4a615666},

doi = {10.1145/3706370.3731643},

isbn = {979-840071391-0 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {IMX - Proc. ACM Int. Conf. Interact. Media Experiences},

pages = {437–440},

publisher = {Association for Computing Machinery, Inc},

abstract = {Virtual Reality has significantly expanded possibilities for immersive museum experiences, overcoming traditional constraints such as space, preservation, and geographic limitations. However, existing virtual museum platforms typically lack dynamic, personalized, and contextually accurate interactions. To address this, we propose Spatially-Aware Retrieval-Augmented Generation (SA-RAG), an innovative framework integrating visual attention tracking with Retrieval-Augmented Generation systems and advanced Large Language Models. By capturing users' visual attention in real time, SA-RAG dynamically retrieves contextually relevant data, enhancing the accuracy, personalization, and depth of user interactions within immersive virtual environments. The system's effectiveness is initially demonstrated through our preliminary tests within a realistic VR museum implemented using Unreal Engine. Although promising, comprehensive human evaluations involving broader user groups are planned for future studies to rigorously validate SA-RAG's effectiveness, educational enrichment potential, and accessibility improvements in virtual museums. The framework also presents opportunities for broader applications in immersive educational and storytelling domains. © 2025 Copyright held by the owner/author(s).},

keywords = {Association reactions, Behavioral Research, Generation systems, Geographics, Human computer interaction, Human engineering, Immersive, Information Retrieval, Interactive computer graphics, Language Model, Large language model, large language models, Museums, Retrieval-Augmented Generation, Search engines, Spatially aware, User interfaces, Virtual environments, Virtual museum, Virtual museum., Virtual Reality, Visual Attention, Visual languages},

pubstate = {published},

tppubtype = {inproceedings}

}

Fernandez, J. A. V.; Lee, J. J.; Vacca, S. A. S.; Magana, A.; Peša, R.; Benes, B.; Popescu, V.

Hands-Free VR Proceedings Article

In: T., Bashford-Rogers; D., Meneveaux; M., Ammi; M., Ziat; S., Jänicke; H., Purchase; P., Radeva; A., Furnari; K., Bouatouch; A.A., Sousa (Ed.): Proc. Int. Jt. Conf. Comput. Vis. Imaging Comput. Graph. Theory Appl., pp. 533–542, Science and Technology Publications, Lda, 2025, ISBN: 21845921 (ISSN).

Abstract | Links | BibTeX | Tags: Deep learning, Large language model, Retrieval-Augmented Generation, Speech-to-Text, Virtual Reality

@inproceedings{fernandez_hands-free_2025,

title = {Hands-Free VR},

author = {J. A. V. Fernandez and J. J. Lee and S. A. S. Vacca and A. Magana and R. Peša and B. Benes and V. Popescu},

editor = {Bashford-Rogers T. and Meneveaux D. and Ammi M. and Ziat M. and Jänicke S. and Purchase H. and Radeva P. and Furnari A. and Bouatouch K. and Sousa A.A.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105001963646&doi=10.5220%2f0013115100003912&partnerID=40&md5=a3f2f4e16bcd5e0579b38e062c987eab},

doi = {10.5220/0013115100003912},

isbn = {21845921 (ISSN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Proc. Int. Jt. Conf. Comput. Vis. Imaging Comput. Graph. Theory Appl.},

volume = {1},

pages = {533–542},

publisher = {Science and Technology Publications, Lda},

abstract = {We introduce Hands-Free VR, a voice-based natural-language interface for VR that allows interaction without additional hardware just using voice. The user voice command is converted into text using a fine-tuned speechto-text deep-learning model. Then, the text is mapped to an executable VR command using an LLM, which is robust to natural language diversity. Hands-Free VR was evaluated in a within-subjects study (N = 22) where participants arranged objects using either a conventional VR interface or Hands-Free VR. The results confirm that Hands-Free VR is: (1) significantly more efficient than conventional VR interfaces in task completion time and user motion metrics; (2) highly rated for ease of use, intuitiveness, ergonomics, reliability, and desirability; (3) robust to English accents (20 participants were non-native speakers) and phonetic similarity, accurately transcribing 96.7% of voice commands, and (3) robust to natural language diversity, mapping 97.83% of transcriptions to executable commands. © 2025 by SCITEPRESS–Science and Technology Publications, Lda.},

keywords = {Deep learning, Large language model, Retrieval-Augmented Generation, Speech-to-Text, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}