Abstract. This study presents an innovative virtual reality (VR) framework for the digital preservation and interactive exploration of Rovigo’s architectural heritage in Italy, focusing on its medieval city walls and their transformation over centuries. By integrating multi-source data fusion (aerial photogrammetry, laser scanning, and close-range photogrammetry), the framework achieves high-precision 3D reconstruction, capturing intricate details at millimeter-level accuracy. The immersive VR experience employs embodied interaction technologies—including gesture recognition (Leap Motion), full-body tracking (HTC Vive), and voice commands—to enable users to engage with historical narratives through hands-on activities such as simulating medieval construction techniques, participating in 19th-century demolition debates, and uncovering hidden traces in residential buildings.The framework combines linear and non-linear storytelling to balance educational rigor with user autonomy, fostering deeper connections to cultural heritage. Key contributions include: (1) a scalable methodology for heritage digitization, demonstrated through Rovigo’s case; and (2) the novel integration of embodied interaction with dynamic narrative design, enhancing engagement and critical reflection on preservation challenges. Preliminary results highlight the potential of VR to bridge the gap between historical documentation and public participation.Limitations, such as data occlusion complexities and scalability for larger sites, are discussed, alongside future directions involving mixed reality (MR), augmented reality (AR), and AI-generated content (AIGC) for personalized storytelling. This research advances digital heritage practices by transforming static monuments into interactive, emotionally resonant experiences while setting a precedent for global applications.
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Pingchuan Ke
Guiye Lin
Yew-Foong Hui
The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
University of Padua
Hong Kong Shue Yan University
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Ke et al. (Wed,) studied this question.
www.synapsesocial.com/papers/68de5da783cbc991d0a20b99 — DOI: https://doi.org/10.5194/isprs-archives-xlviii-m-9-2025-659-2025