AHCI RESEARCH GROUP

Publications

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

OUR RESEARCH

Scientific Publications

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2024

Bao, Y.; Gao, N.; Weng, D.; Chen, J.; Tian, Z.

MuseGesture: A Framework for Gesture Synthesis by Virtual Agents in VR Museum Guides Proceedings Article

In: U., Eck; M., Sra; J., Stefanucci; M., Sugimoto; M., Tatzgern; I., Williams (Ed.): Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct, pp. 337–338, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-833150691-9 (ISBN).

Abstract | Links | BibTeX | Tags: Adversarial machine learning, Embeddings, Gesture Generation, Intelligent Agents, Intelligent systems, Intelligent virtual agents, Language generation, Language Model, Large language model, large language models, Museum guide, Reinforcement Learning, Reinforcement learnings, Robust language understanding, Virtual agent, Virtual Agents, Virtual environments, Virtual reality museum guide, VR Museum Guides

@inproceedings{bao_musegesture_2024,

title = {MuseGesture: A Framework for Gesture Synthesis by Virtual Agents in VR Museum Guides},

author = {Y. Bao and N. Gao and D. Weng and J. Chen and Z. Tian},

editor = {Eck U. and Sra M. and Stefanucci J. and Sugimoto M. and Tatzgern M. and Williams I.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214385900&doi=10.1109%2fISMAR-Adjunct64951.2024.00079&partnerID=40&md5=e71ffc28e299597557034259aab50641},

doi = {10.1109/ISMAR-Adjunct64951.2024.00079},

isbn = {979-833150691-9 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct},

pages = {337–338},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {This paper presents an innovative framework named MuseGesture, designed to generate contextually adaptive gestures for virtual agents in Virtual Reality (VR) museums. The framework leverages the robust language understanding and generation capabilities of Large Language Models (LLMs) to parse tour narration texts and generate corresponding explanatory gestures. Through reinforcement learning and adversarial skill embeddings, the framework also generates guiding gestures tailored to the virtual museum environment, integrating both gesture types using conditional motion interpolation methods. Experimental results and user studies demonstrate that this approach effectively enables voice-command-controlled virtual guide gestures, offering a novel intelligent guiding system solution that enhances the interactive experience in VR museum environments. © 2024 IEEE.},

keywords = {Adversarial machine learning, Embeddings, Gesture Generation, Intelligent Agents, Intelligent systems, Intelligent virtual agents, Language generation, Language Model, Large language model, large language models, Museum guide, Reinforcement Learning, Reinforcement learnings, Robust language understanding, Virtual agent, Virtual Agents, Virtual environments, Virtual reality museum guide, VR Museum Guides},

pubstate = {published},

tppubtype = {inproceedings}

}

2023

Fuchs, A.; Appel, S.; Grimm, P.

Immersive Spaces for Creativity: Smart Working Environments Proceedings Article

In: A.A., Yunanto; A.D., Ramadhani; Y.R., Prayogi; P.A.M., Putra; M., Ruswiansari; M., Ridwan; F., Gamar; W.M., Rahmawati; M.R., Rusli; F.M., Humaira; A.F., Adila (Ed.): IES - Int. Electron. Symp.: Unlocking Potential Immersive Technol. Live Better Life, Proceeding, pp. 610–617, Institute of Electrical and Electronics Engineers Inc., 2023, ISBN: 979-835031473-1 (ISBN).

Abstract | Links | BibTeX | Tags: Artificial intelligence, Generative AI, Human computer interaction, Immersive, Innovative approaches, Intelligent systems, Interactive Environments, Language Model, Language processing, Large language model, large language models, Learning algorithms, machine learning, Natural language processing systems, Natural languages, User behaviors, User interfaces, Virtual Reality, Working environment

@inproceedings{fuchs_immersive_2023,

title = {Immersive Spaces for Creativity: Smart Working Environments},

author = {A. Fuchs and S. Appel and P. Grimm},

editor = {Yunanto A.A. and Ramadhani A.D. and Prayogi Y.R. and Putra P.A.M. and Ruswiansari M. and Ridwan M. and Gamar F. and Rahmawati W.M. and Rusli M.R. and Humaira F.M. and Adila A.F.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173627291&doi=10.1109%2fIES59143.2023.10242458&partnerID=40&md5=6ab1796f68c29d7747574272314a2e9d},

doi = {10.1109/IES59143.2023.10242458},

isbn = {979-835031473-1 (ISBN)},

year  = {2023},

date = {2023-01-01},

booktitle = {IES - Int. Electron. Symp.: Unlocking Potential Immersive Technol. Live Better Life, Proceeding},

pages = {610–617},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {This paper presents an innovative approach to designing an immersive space that dynamically supports users (inter-)action based on users' behavior, voice, and mood, providing a personalized experience. The objective of this research is to explore how a space can communicate with users in a seamless, engaging, and interactive environment. Therefore, it integrates natural language processing (NLP), generative artificial intelligence applications and human computer interaction that utilizes a combination of sensors, microphones, and cameras to collect real-time data on users' behavior, voice, and mood. This data is then processed and analyzed by an intelligent system that employs machine learning algorithms to identify patterns and adapt the environment accordingly. The adaptive features include changes in lighting, sound, and visual elements to facilitate creativity, focus, relaxation, or socialization, depending on the user's topics and emotional state. The paper discusses the technical aspects of implementing such a system. Additionally, it highlights the potential applications of this technology in various domains such as education, entertainment, and workplace settings. In conclusion, the immersive creative space represents a paradigm shift in human-environment interaction, offering a dynamic and personalized space that caters to the diverse needs of users. The research findings suggest that this innovative approach holds great promise for enhancing user experiences, fostering creativity, and promoting overall well-being. © 2023 IEEE.},

keywords = {Artificial intelligence, Generative AI, Human computer interaction, Immersive, Innovative approaches, Intelligent systems, Interactive Environments, Language Model, Language processing, Large language model, large language models, Learning algorithms, machine learning, Natural language processing systems, Natural languages, User behaviors, User interfaces, Virtual Reality, Working environment},

pubstate = {published},

tppubtype = {inproceedings}

}