3D Data Analysis of Archaeological Ceramics
Organizers’ contacts:
University of L’Aquila, Department of Industrial and Information Engineering and Economics (DIIIE)
Piazzale Ernesto Pontieri, 1 – 67100 Monteluco di Roio (AQ), Italy
E-mails:
luca.diangelo@univaq.it
paolo.distefano@univaq.it
emanuele.guardiani@univaq.it
antonio.marzola@univaq.it
Abstract
This special session focuses on contributions related to the 3D data analysis of archaeological ceramics and their application in addressing current research challenges in the study of ancient pottery. Pottery is the most commonly recovered artefact in archaeological excavations and is fundamental for reconstructing a site’s history, economy, and artistic production. Archaeologists rarely find complete vessels; instead, pottery is often discovered in a fragmentary state, frequently mixed with sherds from other assemblages.
Traditional techniques for pottery reconstruction and preservation are time-consuming and non-reproducible, as they heavily depend on the operator’s manual skills and experience. For these reasons, such methods have been increasingly supplemented, and in some cases replaced, by digital approaches, which have introduced new, transformative possibilities for archaeological documentation and restoration.
The contributions presented in this session should focus on innovative 3D data analysis methods aimed at automating the processing, analysis, and interpretation of ceramic artefacts, particularly sherds. Emphasis should be placed on computer-based methodologies that integrate archaeological expertise with advanced 3D data processing and pattern recognition techniques. Ultimately, these approaches will enable a deeper understanding of ancient craftsmanship and production techniques, help address specific archaeological questions, and foster the development of methodologies for managing and interpreting large-scale archaeological datasets.
Topics of Interest
- Geometrical and morphological segmentation
- Shape analysis
- Pottery classification
- Ceramics reconstruction from fragments
- Detection of characteristic dimensions
- Axis estimation and grouping of pottery segments
