Holo-Artisan: A Personalized Multi-User Holographic Experience for Virtual Museums on the Edge Intelligence
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866916910614970368 |
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| author | Kuo, Nan-Hong Baghban, Hojjat |
| author_facet | Kuo, Nan-Hong Baghban, Hojjat |
| contents | We present Holo-Artisan, a novel system architecture enabling immersive multi-user experiences in virtual museums through true holographic displays and personalized edge intelligence. In our design, local edge computing nodes process real-time user data -- including pose, facial expression, and voice -- for multiple visitors concurrently. Generative AI models then drive digital artworks (e.g., a volumetric Mona Lisa) to respond uniquely to each viewer. For instance, the Mona Lisa can return a smile to one visitor while engaging in a spoken Q\&A with another, all in real time. A cloud-assisted collaboration platform composes these interactions in a shared scene using a universal scene description, and employs ray tracing to render high-fidelity, personalized views with a direct pipeline to glasses-free holographic displays. To preserve user privacy and continuously improve personalization, we integrate federated learning (FL) -- edge devices locally fine-tune AI models and share only model updates for aggregation. This edge-centric approach minimizes latency and bandwidth usage, ensuring a synchronized shared experience with individual customization. Through Holo-Artisan, static museum exhibits are transformed into dynamic, living artworks that engage each visitor in a personal dialogue, heralding a new paradigm of cultural heritage interaction. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_14956 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Holo-Artisan: A Personalized Multi-User Holographic Experience for Virtual Museums on the Edge Intelligence Kuo, Nan-Hong Baghban, Hojjat Multimedia Networking and Internet Architecture Systems and Control Image and Video Processing We present Holo-Artisan, a novel system architecture enabling immersive multi-user experiences in virtual museums through true holographic displays and personalized edge intelligence. In our design, local edge computing nodes process real-time user data -- including pose, facial expression, and voice -- for multiple visitors concurrently. Generative AI models then drive digital artworks (e.g., a volumetric Mona Lisa) to respond uniquely to each viewer. For instance, the Mona Lisa can return a smile to one visitor while engaging in a spoken Q\&A with another, all in real time. A cloud-assisted collaboration platform composes these interactions in a shared scene using a universal scene description, and employs ray tracing to render high-fidelity, personalized views with a direct pipeline to glasses-free holographic displays. To preserve user privacy and continuously improve personalization, we integrate federated learning (FL) -- edge devices locally fine-tune AI models and share only model updates for aggregation. This edge-centric approach minimizes latency and bandwidth usage, ensuring a synchronized shared experience with individual customization. Through Holo-Artisan, static museum exhibits are transformed into dynamic, living artworks that engage each visitor in a personal dialogue, heralding a new paradigm of cultural heritage interaction. |
| title | Holo-Artisan: A Personalized Multi-User Holographic Experience for Virtual Museums on the Edge Intelligence |
| topic | Multimedia Networking and Internet Architecture Systems and Control Image and Video Processing |
| url | https://arxiv.org/abs/2508.14956 |