AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
Arai, K.
Digital Twin Model from Freehanded Sketch to Facade Design, 2D-3D Conversion for Volume Design Journal Article
In: International Journal of Advanced Computer Science and Applications, vol. 16, no. 1, pp. 88–95, 2025, ISSN: 2158107X (ISSN).
Abstract | Links | BibTeX | Tags: 2D/3D conversion, AI, Architectural design, BIM, Digital Twins, Facade design, Facades, GauGAN, Generative AI, GeoTiff, GIS, IFC format, Metaverse, Metaverses, SketchUp, TriPo, Volume design, Volume Rendering
@article{arai_digital_2025,
title = {Digital Twin Model from Freehanded Sketch to Facade Design, 2D-3D Conversion for Volume Design},
author = {K. Arai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216872163&doi=10.14569%2fIJACSA.2025.0160109&partnerID=40&md5=fd4e69f9b20d86e3b5d07b4cdcb00b2d},
doi = {10.14569/IJACSA.2025.0160109},
issn = {2158107X (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {International Journal of Advanced Computer Science and Applications},
volume = {16},
number = {1},
pages = {88–95},
abstract = {The article proposes a method for creating digital twins from freehand sketches for facade design, converting 2D designs to 3D volumes, and integrating these designs into real-world GIS systems. It outlines a process that involves generating 2D exterior images from sketches using generative AI (Gemini 1.5 Pro), converting these 2D images into 3D models with TriPo, and creating design drawings with SketchUp. Additionally, it describes a method for creating 3D exterior images using GauGAN, all for the purpose of construction exterior evaluation. The paper also discusses generating BIM data using generative AI, converting BIM data (in IFC file format) to GeoTiff, and displaying this information in GIS using QGIS software. Moreover, it suggests a method for generating digital twins with SketchUp to facilitate digital design information sharing and simulation within a virtual space. Lastly, it advocates for a cost-effective AI system designed for small and medium-sized construction companies, which often struggle to adopt BIM, to harness the advantages of digital twins. © (2025), (Science and Information Organization). All rights reserved.},
keywords = {2D/3D conversion, AI, Architectural design, BIM, Digital Twins, Facade design, Facades, GauGAN, Generative AI, GeoTiff, GIS, IFC format, Metaverse, Metaverses, SketchUp, TriPo, Volume design, Volume Rendering},
pubstate = {published},
tppubtype = {article}
}
The article proposes a method for creating digital twins from freehand sketches for facade design, converting 2D designs to 3D volumes, and integrating these designs into real-world GIS systems. It outlines a process that involves generating 2D exterior images from sketches using generative AI (Gemini 1.5 Pro), converting these 2D images into 3D models with TriPo, and creating design drawings with SketchUp. Additionally, it describes a method for creating 3D exterior images using GauGAN, all for the purpose of construction exterior evaluation. The paper also discusses generating BIM data using generative AI, converting BIM data (in IFC file format) to GeoTiff, and displaying this information in GIS using QGIS software. Moreover, it suggests a method for generating digital twins with SketchUp to facilitate digital design information sharing and simulation within a virtual space. Lastly, it advocates for a cost-effective AI system designed for small and medium-sized construction companies, which often struggle to adopt BIM, to harness the advantages of digital twins. © (2025), (Science and Information Organization). All rights reserved.
Behravan, M.; Gračanin, D.
From Voices to Worlds: Developing an AI-Powered Framework for 3D Object Generation in Augmented Reality Proceedings Article
In: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW, pp. 150–155, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 979-833151484-6 (ISBN).
Abstract | Links | BibTeX | Tags: 3D modeling, 3D object, 3D Object Generation, 3D reconstruction, Augmented Reality, Cutting edges, Generative AI, Interactive computer systems, Language Model, Large language model, large language models, matrix, Multilingual speech interaction, Real- time, Speech enhancement, Speech interaction, Volume Rendering
@inproceedings{behravan_voices_2025,
title = {From Voices to Worlds: Developing an AI-Powered Framework for 3D Object Generation in Augmented Reality},
author = {M. Behravan and D. Gračanin},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005153589&doi=10.1109%2fVRW66409.2025.00038&partnerID=40&md5=b8aaab4e2378cde3595d98d79266d371},
doi = {10.1109/VRW66409.2025.00038},
isbn = {979-833151484-6 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW},
pages = {150–155},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {This paper presents Matrix, an advanced AI-powered framework designed for real-time 3D object generation in Augmented Reality (AR) environments. By integrating a cutting-edge text-to-3D generative AI model, multilingual speech-to-text translation, and large language models (LLMs), the system enables seamless user interactions through spoken commands. The framework processes speech inputs, generates 3D objects, and provides object recommendations based on contextual understanding, enhancing AR experiences. A key feature of this framework is its ability to optimize 3D models by reducing mesh complexity, resulting in significantly smaller file sizes and faster processing on resource-constrained AR devices. Our approach addresses the challenges of high GPU usage, large model output sizes, and real-time system responsiveness, ensuring a smoother user experience. Moreover, the system is equipped with a pre-generated object repository, further reducing GPU load and improving efficiency. We demonstrate the practical applications of this framework in various fields such as education, design, and accessibility, and discuss future enhancements including image-to-3D conversion, environmental object detection, and multimodal support. The open-source nature of the framework promotes ongoing innovation and its utility across diverse industries. © 2025 IEEE.},
keywords = {3D modeling, 3D object, 3D Object Generation, 3D reconstruction, Augmented Reality, Cutting edges, Generative AI, Interactive computer systems, Language Model, Large language model, large language models, matrix, Multilingual speech interaction, Real- time, Speech enhancement, Speech interaction, Volume Rendering},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper presents Matrix, an advanced AI-powered framework designed for real-time 3D object generation in Augmented Reality (AR) environments. By integrating a cutting-edge text-to-3D generative AI model, multilingual speech-to-text translation, and large language models (LLMs), the system enables seamless user interactions through spoken commands. The framework processes speech inputs, generates 3D objects, and provides object recommendations based on contextual understanding, enhancing AR experiences. A key feature of this framework is its ability to optimize 3D models by reducing mesh complexity, resulting in significantly smaller file sizes and faster processing on resource-constrained AR devices. Our approach addresses the challenges of high GPU usage, large model output sizes, and real-time system responsiveness, ensuring a smoother user experience. Moreover, the system is equipped with a pre-generated object repository, further reducing GPU load and improving efficiency. We demonstrate the practical applications of this framework in various fields such as education, design, and accessibility, and discuss future enhancements including image-to-3D conversion, environmental object detection, and multimodal support. The open-source nature of the framework promotes ongoing innovation and its utility across diverse industries. © 2025 IEEE.
Mao, H.; Xu, Z.; Wei, S.; Quan, Y.; Deng, N.; Yang, X.
LLM-powered Gaussian Splatting in VR interactions Proceedings Article
In: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW, pp. 1654–1655, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 979-833151484-6 (ISBN).
Abstract | Links | BibTeX | Tags: 3D Gaussian Splatting, 3D reconstruction, Content creation, Digital elevation model, Gaussians, High quality, Language Model, material analysis, Materials analysis, Physical simulation, Quality rendering, Rendering (computer graphics), Splatting, Virtual Reality, Volume Rendering, VR systems
@inproceedings{mao_llm-powered_2025,
title = {LLM-powered Gaussian Splatting in VR interactions},
author = {H. Mao and Z. Xu and S. Wei and Y. Quan and N. Deng and X. Yang},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005148017&doi=10.1109%2fVRW66409.2025.00472&partnerID=40&md5=ee725f655a37251ff335ad2098d15f22},
doi = {10.1109/VRW66409.2025.00472},
isbn = {979-833151484-6 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW},
pages = {1654–1655},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Recent advances in radiance field rendering, particularly 3D Gaussian Splatting (3DGS), have demonstrated significant potential for VR content creation, offering both high-quality rendering and an efficient production pipeline. However, current physics-based interaction systems for 3DGS are limited to either simplistic, unrealistic simulations or require substantial user input for complex scenes, largely due to the lack of scene comprehension. In this demonstration, we present a highly realistic interactive VR system powered by large language models (LLMs). After object-aware GS reconstruction, we prompt GPT-4o to analyze the physical properties of objects in the scene, which then guide physical simulations that adhere to real-world phenomena. Additionally, We design a GPT-assisted GS inpainting module to complete the areas occluded by manipulated objects. To facilitate rich interaction, we introduce a computationally efficient physical simulation framework through a PBD-based unified interpolation method, which supports various forms of physical interactions. In our research demonstrations, we reconstruct varieties of scenes enhanced by LLM's understanding, showcasing how our VR system can support complex, realistic interactions without additional manual design or annotation. © 2025 IEEE.},
keywords = {3D Gaussian Splatting, 3D reconstruction, Content creation, Digital elevation model, Gaussians, High quality, Language Model, material analysis, Materials analysis, Physical simulation, Quality rendering, Rendering (computer graphics), Splatting, Virtual Reality, Volume Rendering, VR systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Recent advances in radiance field rendering, particularly 3D Gaussian Splatting (3DGS), have demonstrated significant potential for VR content creation, offering both high-quality rendering and an efficient production pipeline. However, current physics-based interaction systems for 3DGS are limited to either simplistic, unrealistic simulations or require substantial user input for complex scenes, largely due to the lack of scene comprehension. In this demonstration, we present a highly realistic interactive VR system powered by large language models (LLMs). After object-aware GS reconstruction, we prompt GPT-4o to analyze the physical properties of objects in the scene, which then guide physical simulations that adhere to real-world phenomena. Additionally, We design a GPT-assisted GS inpainting module to complete the areas occluded by manipulated objects. To facilitate rich interaction, we introduce a computationally efficient physical simulation framework through a PBD-based unified interpolation method, which supports various forms of physical interactions. In our research demonstrations, we reconstruct varieties of scenes enhanced by LLM's understanding, showcasing how our VR system can support complex, realistic interactions without additional manual design or annotation. © 2025 IEEE.
2007
Pietro, Giuseppe De; Gallo, Luigi; Marra, Ivana; Vanzanella, Carmen
A New Approach for Handling 3D Medical Data in an Immersive Environment Proceedings Article
In: VECIMS 2007. IEEE Symposium on Virtual Environments, Human-Computer Interfaces and Measurement Systems, 2007, pp. 63–66, IEEE Computer Society, Ostuni, Italy, 2007, ISBN: 978-1-4244-0820-7.
Abstract | Links | BibTeX | Tags: Healthcare, Medical Imaging, VOI, Volume Rendering, VTK
@inproceedings{depietroNewApproachHandling2007,
title = {A New Approach for Handling 3D Medical Data in an Immersive Environment},
author = { Giuseppe De Pietro and Luigi Gallo and Ivana Marra and Carmen Vanzanella},
doi = {10.1109/VECIMS.2007.4373929},
isbn = {978-1-4244-0820-7},
year = {2007},
date = {2007-06-01},
booktitle = {VECIMS 2007. IEEE Symposium on Virtual Environments, Human-Computer Interfaces and Measurement Systems, 2007},
pages = {63--66},
publisher = {IEEE Computer Society},
address = {Ostuni, Italy},
abstract = {Medical Imaging applications use images coming from different sources such as magnetic resonance imaging (MRI), computer tomography (CT), positron emission tomography (PET), to generate 3D data. Starting from these volumetric data, applications reconstruct 3D models of anatomical structures which could be manipulated and analyzed. In this paper we present a new approach for the visualization and interaction with volumetric datasets in a fully immersive environment. It allows to handle the reconstructed models directly within the virtual scene; in particular a technique is described for outlining the Volume Of Interest (VOI) functionality in a three-dimensional dataset for a visual interactive inspection and manipulation of the organ of interest.},
keywords = {Healthcare, Medical Imaging, VOI, Volume Rendering, VTK},
pubstate = {published},
tppubtype = {inproceedings}
}
Medical Imaging applications use images coming from different sources such as magnetic resonance imaging (MRI), computer tomography (CT), positron emission tomography (PET), to generate 3D data. Starting from these volumetric data, applications reconstruct 3D models of anatomical structures which could be manipulated and analyzed. In this paper we present a new approach for the visualization and interaction with volumetric datasets in a fully immersive environment. It allows to handle the reconstructed models directly within the virtual scene; in particular a technique is described for outlining the Volume Of Interest (VOI) functionality in a three-dimensional dataset for a visual interactive inspection and manipulation of the organ of interest.
Pietro, Giuseppe De; Gallo, Luigi; Marra, Ivana; Vanzanella, Carmen
A New Approach for Handling 3D Medical Data in an Immersive Environment Proceedings Article
In: VECIMS 2007. IEEE Symposium on Virtual Environments, Human-Computer Interfaces and Measurement Systems, 2007, pp. 63–66, IEEE Computer Society, Ostuni, Italy, 2007, ISBN: 978-1-4244-0820-7.
Abstract | Links | BibTeX | Tags: Healthcare, Medical Imaging, VOI, Volume Rendering, VTK
@inproceedings{de_pietro_new_2007,
title = {A New Approach for Handling 3D Medical Data in an Immersive Environment},
author = {Giuseppe De Pietro and Luigi Gallo and Ivana Marra and Carmen Vanzanella},
doi = {10.1109/VECIMS.2007.4373929},
isbn = {978-1-4244-0820-7},
year = {2007},
date = {2007-06-01},
booktitle = {VECIMS 2007. IEEE Symposium on Virtual Environments, Human-Computer Interfaces and Measurement Systems, 2007},
pages = {63–66},
publisher = {IEEE Computer Society},
address = {Ostuni, Italy},
abstract = {Medical Imaging applications use images coming from different sources such as magnetic resonance imaging (MRI), computer tomography (CT), positron emission tomography (PET), to generate 3D data. Starting from these volumetric data, applications reconstruct 3D models of anatomical structures which could be manipulated and analyzed. In this paper we present a new approach for the visualization and interaction with volumetric datasets in a fully immersive environment. It allows to handle the reconstructed models directly within the virtual scene; in particular a technique is described for outlining the Volume Of Interest (VOI) functionality in a three-dimensional dataset for a visual interactive inspection and manipulation of the organ of interest.},
keywords = {Healthcare, Medical Imaging, VOI, Volume Rendering, VTK},
pubstate = {published},
tppubtype = {inproceedings}
}
Medical Imaging applications use images coming from different sources such as magnetic resonance imaging (MRI), computer tomography (CT), positron emission tomography (PET), to generate 3D data. Starting from these volumetric data, applications reconstruct 3D models of anatomical structures which could be manipulated and analyzed. In this paper we present a new approach for the visualization and interaction with volumetric datasets in a fully immersive environment. It allows to handle the reconstructed models directly within the virtual scene; in particular a technique is described for outlining the Volume Of Interest (VOI) functionality in a three-dimensional dataset for a visual interactive inspection and manipulation of the organ of interest.