This paper presents an approach for documenting historical phases in architectural heritage by implementing unsupervised Machine Learning (ML). We employ the RANSAC algorithm for architectural segmentation and K-means to analyze the historical sequence in point clouds using geometric features. Finally, the Extended Matrix (EM) tool within a native IFC environment is used for the archaeological metadata linkage standardization. We have tested our approach using several constructive elements of the San Isidoro complex, in León (Spain).
AI-Driven Analysis in Point Clouds for Archaeological Documentation / Munoz Cadiz, Jesus; Quattrini, Ramona; Martin-Talaverano, Rafael. - ELETTRONICO. - (2025), pp. 83-96. [10.1007/978-3-031-93753-8_6]
AI-Driven Analysis in Point Clouds for Archaeological Documentation
Jesus Munoz- Cadiz
;Ramona Quattrini;
2025-01-01
Abstract
This paper presents an approach for documenting historical phases in architectural heritage by implementing unsupervised Machine Learning (ML). We employ the RANSAC algorithm for architectural segmentation and K-means to analyze the historical sequence in point clouds using geometric features. Finally, the Extended Matrix (EM) tool within a native IFC environment is used for the archaeological metadata linkage standardization. We have tested our approach using several constructive elements of the San Isidoro complex, in León (Spain).| File | Dimensione | Formato | |
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