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D reconstruction of cultural heritage sites; A case study of Patan Durbar Square

Bibliographic Data

ID6639089
AuthorsPratik Shrestha (Tribhuvan University), Subarna Prasad Kapali, Sujan Kapali (Tribhuvan University), Vishal Pokharel (Tribhuvan University), Jyoti Tandukar (Tribhuvan University), Giri (0000-0002-5186-7814, Tribhuvan University, corresponding author), Santosh Giri (0009-0003-0577-7345), Amrit Aryal (Tribhuvan University)
Year2025
Volume40
Pagese00492-e00492
Publication date2025-12-01
Open AccessYes
TypeARTICLE
VenueDigital Applications in Archaeology and Cultural Heritage (JOURNAL)
Journal identifiersISSN: 2212-0548
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.daach.2025.e00492
OpenAlexW4417504975
LanguageEN
Citations received1
References cited20

Over time, cultural heritage sites deteriorate, making it vital to document their original state for future generations. We present an efficient system for 3D modeling and reconstruction of cultural heritage, demonstrated on Patan Durbar Square. Short video clips were captured from various angles using an iPhone 13, and individual frames were extracted to form overlapping datasets of about 900–1300 frames per site. Using COLMAP for camera pose and sparse point cloud estimation, Gaussian splatting reconstructed both geometry and appearance. However, the baseline implementation introduced artifacts and required extensive training. We therefore evaluated multiple strategies, including Splatfacto and artifact removal and segmentation methods. Combining GroundingDINO and SAM effectively removed people and birds, while Splatfacto with masking and bilateral grids produced high-quality reconstructions. The proposed pipeline enables accurate, scalable, and efficient 3D documentation of cultural heritage sites.

3D reconstruction · Artifact (error) · Cultural heritage · Documentation · Masking (illustration) · Pipeline (software) · Point (geometry) · Point cloud · Segmentation · 3D Surveying and Cultural Heritage · Image Processing and 3D Reconstruction · Robotics and Sensor-Based Localization

  • Convergence behaviour and computational efficiency of Gaussian Splatting in complex heritage environments

    Open Access•Rafael Ortiz-Cordero, Rafael Enrique Hidalgo Fernández•Virtual Archaeology Review•2026

  • Learning representations by back-propagating errors

    Open Access•David E Rumelhart, Geoffrey E Hinton et al.•Nature•1986

  • Random sample consensus

    Open Access•Martin A Fischler, Robert C Bolles•Communications of the ACM•1981

Citations per year1
Citation span2026 - 2026 (1)
Highly citedNo

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Open DOIOpen Access
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