Publications

@inproceedings{behravan_transcending_2025,

title = {Transcending Dimensions Using Generative AI: Real-Time 3D Model Generation in Augmented Reality},

author = {M. Behravan and M. Haghani and D. Gračanin},

editor = {Chen J.Y.C. and Fragomeni G.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007690904&doi=10.1007%2f978-3-031-93700-2_2&partnerID=40&md5=1c4d643aad88d08cbbc9dd2c02413f10},

doi = {10.1007/978-3-031-93700-2_2},

isbn = {03029743 (ISSN); 978-303193699-9 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Lect. Notes Comput. Sci.},

volume = {15788 LNCS},

pages = {13–32},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {Traditional 3D modeling requires technical expertise, specialized software, and time-intensive processes, making it inaccessible for many users. Our research aims to lower these barriers by combining generative AI and augmented reality (AR) into a cohesive system that allows users to easily generate, manipulate, and interact with 3D models in real time, directly within AR environments. Utilizing cutting-edge AI models like Shap-E, we address the complex challenges of transforming 2D images into 3D representations in AR environments. Key challenges such as object isolation, handling intricate backgrounds, and achieving seamless user interaction are tackled through advanced object detection methods, such as Mask R-CNN. Evaluation results from 35 participants reveal an overall System Usability Scale (SUS) score of 69.64, with participants who engaged with AR/VR technologies more frequently rating the system significantly higher, at 80.71. This research is particularly relevant for applications in gaming, education, and AR-based e-commerce, offering intuitive, model creation for users without specialized skills. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},

keywords = {3D Model Generation, 3D modeling, 3D models, 3d-modeling, Augmented Reality, Generative AI, Image-to-3D conversion, Model generation, Object Detection, Object recognition, Objects detection, Real- time, Specialized software, Technical expertise, Three dimensional computer graphics, Usability engineering},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{lau_evaluating_2025,

title = {Evaluating Usability and Engagement of Large Language Models in Virtual Reality for Traditional Scottish Curling},

author = {K. H. C. Lau and E. Bozkir and H. Gao and E. Kasneci},

editor = {Del Bue A. and Canton C. and Pont-Tuset J. and Tommasi T.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105006905979&doi=10.1007%2f978-3-031-91572-7_11&partnerID=40&md5=8a81fb09ff54e57b9429660a8898149a},

doi = {10.1007/978-3-031-91572-7_11},

isbn = {03029743 (ISSN); 978-303191571-0 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Lect. Notes Comput. Sci.},

volume = {15628 LNCS},

pages = {177–195},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {This paper explores the innovative application of Large Language Models (LLMs) in Virtual Reality (VR) environments to promote heritage education, focusing on traditional Scottish curling presented in the game “Scottish Bonspiel VR”. Our study compares the effectiveness of LLM-based chatbots with pre-defined scripted chatbots, evaluating key criteria such as usability, user engagement, and learning outcomes. The results show that LLM-based chatbots significantly improve interactivity and engagement, creating a more dynamic and immersive learning environment. This integration helps document and preserve cultural heritage and enhances dissemination processes, which are crucial for safeguarding intangible cultural heritage (ICH) amid environmental changes. Furthermore, the study highlights the potential of novel technologies in education to provide immersive experiences that foster a deeper appreciation of cultural heritage. These findings support the wider application of LLMs and VR in cultural education to address global challenges and promote sustainable practices to preserve and enhance cultural heritage. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},

keywords = {Chatbots, Cultural heritages, Digital Cultural Heritage, Digital cultural heritages, Educational robots, Engineering education, Heritage education, Historic Preservation, Language Model, Large language model, large language models, Learning outcome, Model-based OPC, Usability engineering, User Engagement, Virtual Reality, Virtual-reality environment, Virtualization},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{zhang_fusionprotor_2025,

title = {FusionProtor: A Mixed-Prototype Tool for Component-level Physical-to-Virtual 3D Transition and Simulation},

author = {H. Zhang and P. Chen and X. Xie and Z. Jiang and Y. Wu and Z. Li and X. Chen and L. Sun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005745450&doi=10.1145%2f3706598.3713686&partnerID=40&md5=e51eac0cc99293538422d98a4070cd09},

doi = {10.1145/3706598.3713686},

isbn = {979-840071394-1 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Conf Hum Fact Comput Syst Proc},

publisher = {Association for Computing Machinery},

abstract = {Developing and simulating 3D prototypes is crucial in product conceptual design for ideation and presentation. Traditional methods often keep physical and virtual prototypes separate, leading to a disjointed prototype workflow. In addition, acquiring high-fidelity prototypes is time-consuming and resource-intensive, distracting designers from creative exploration. Recent advancements in generative artificial intelligence (GAI) and extended reality (XR) provided new solutions for rapid prototype transition and mixed simulation. We conducted a formative study to understand current challenges in the traditional prototype process and explore how to effectively utilize GAI and XR ability in prototype. Then we introduced FusionProtor, a mixed-prototype tool for component-level 3D prototype transition and simulation. We proposed a step-by-step generation pipeline in FusionProtor, effectively transiting 3D prototypes from physical to virtual and low- to high-fidelity for rapid ideation and iteration. We also innovated a component-level 3D creation method and applied it in XR environment for the mixed-prototype presentation and interaction. We conducted technical and user experiments to verify FusionProtor's usability in supporting diverse designs. Our results verified that it achieved a seamless workflow between physical and virtual domains, enhancing efficiency and promoting ideation. We also explored the effect of mixed interaction on design and critically discussed its best practices for HCI community. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.},

keywords = {3D modeling, 3D prototype, 3D simulations, 3d transition, Component levels, Conceptual design, Creatives, Generative AI, High-fidelity, Integrated circuit layout, Mixed reality, Product conceptual designs, Prototype tools, Prototype workflow, Three dimensional computer graphics, Usability engineering, Virtual Prototyping},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{harinee_elevating_2024,

title = {Elevating Medical Training: A Synergistic Fusion of AI and VR for Immersive Anatomy Learning and Practical Procedure Mastery},

author = {S. Harinee and R. Vimal Raja and E. Mugila and I. Govindharaj and V. Sanjaykumar and T. Ragavendhiran},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105000334626&doi=10.1109%2fICSCAN62807.2024.10894451&partnerID=40&md5=100899b489c00335e0a652f2efd33e23},

doi = {10.1109/ICSCAN62807.2024.10894451},

isbn = {979-833151002-2 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Int. Conf. Syst., Comput., Autom. Netw., ICSCAN},

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

abstract = {Virtual reality with its 3D visualization have brought an overwhelming change in the face of medical education, especially for courses like human anatomy. The proposed virtual reality system to bring massive improvements in the education received by a medical student studying for their degree courses. The project puts forward the text-to-speech and speech-to-text aligned system that simplifies the usage of a chatbot empowered by OpenAI GPT-4 and allows pupils to vocally speak with Avatar, the set virtual assistant. Contrary to the current methodologies, the setup of virtual reality is powered by avatars and thus covers an enhanced virtual assistant environment. Avatars offer students the set of repeated practicing of medical procedures on it, and the real uniqueness in the proposed product. The developed virtual reality environment is enhanced over other current training techniques where a student should interact and immerse in three-dimensional human organs for visualization in three dimensions and hence get better knowledge of the subjects in greater depth. A virtual assistant guides the whole process, giving insights and support to help the student bridge the gap from theory to practice. Then, the system is essentially Knowledge based and Analysis based approach. The combination of generative AI along with embodied virtual agents has great potential when it comes to customized virtual conversation assistant for much wider range of applications. The study brings out the value of acquiring hands-on skills through simulated medical procedures and opens new frontiers of research and development in AI, VR, and medical education. In addition to assessing the effectiveness of such novel functionalities, the study also explores user experience related dimensions such as usability, task loading, and the sense of presence in proposed virtual medical environment. © 2024 IEEE.},

keywords = {'current, Anatomy education, Anatomy educations, Computer interaction, Curricula, Embodied virtual assistant, Embodied virtual assistants, Generative AI, Human- Computer Interaction, Immersive, Intelligent virtual agents, Medical computing, Medical education, Medical procedure practice, Medical procedures, Medical training, Personnel training, Students, Teaching, Three dimensional computer graphics, Usability engineering, Virtual assistants, Virtual environments, Virtual Reality, Visualization},

pubstate = {published},

tppubtype = {inproceedings}

}