<p>Virtual reconstruction of cultural heritage sites enables historical presentation without physical intervention, supporting research and public education. Current methods use color-coded evidence scales but fail to clarify how diverse sources contribute to specific reconstruction features like geometry, texture, or spatial position. This study proposes a Source-Feature Matrix (SFM) integrating evidence sources and reconstruction features into a structured framework. To demonstrate the advantage of SFM in interpreting virtual reconstruction results, this paper takes the Diqi Altar in architecture groups of Xiannong Altar (Altar of Agriculture in Beijing) as a case study. It assesses the strength of reconstruction evidence support for geometric shape, texture color, and spatial position of objects in the site using the SFM method. The results show that the SFM method can help assess the support strength of virtual reconstruction evidence and enhance the interpretability of virtual reconstruction results.</p>

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Using Source Feature Matrix for interpreting the result in virtual reconstruction of cultural heritage sites

  • Xinyang Liu,
  • Su Yang,
  • Caochenyu Zhou,
  • Ziyu Guo,
  • Tao Zhang,
  • Miaole Hou

摘要

Virtual reconstruction of cultural heritage sites enables historical presentation without physical intervention, supporting research and public education. Current methods use color-coded evidence scales but fail to clarify how diverse sources contribute to specific reconstruction features like geometry, texture, or spatial position. This study proposes a Source-Feature Matrix (SFM) integrating evidence sources and reconstruction features into a structured framework. To demonstrate the advantage of SFM in interpreting virtual reconstruction results, this paper takes the Diqi Altar in architecture groups of Xiannong Altar (Altar of Agriculture in Beijing) as a case study. It assesses the strength of reconstruction evidence support for geometric shape, texture color, and spatial position of objects in the site using the SFM method. The results show that the SFM method can help assess the support strength of virtual reconstruction evidence and enhance the interpretability of virtual reconstruction results.