Schemata. 3D Classification and Categorisation of Ancient Terracotta Figurines

PROJECT ABSTRACT

The goal of the proposed case-study is not only to develop procedures for automatically generating corpora using 3D pattern recognition, but also to reflect on the associated schematizations and how they can be applied to the computer and visual sciences. Based on 200 terracottas of the late 4th and 3rd centuries BC, which are quite similar to each other, digital methods will be used to create a classification system able to do justice to the complexity of the artefacts. For this purpose, it is intended to develop methods of object-mining in 3D data that support the search for a suitable classification and categorization of the images. In close cooperation between computer science and archaeology, this experimental process will lead to a fundamental examination of the concept of pattern recognition as a humanities category. The discussion of the various concepts and methods will be carried out in two complementary dissertations on “Classifications and Categorizations with Digital Methods: Consistency and Variation in the Shapes of Hellenistic Terracottas of Women,” and “3D Shape Analysis of Ancient Terracottas: Contributions to Automated Object Mining”.

TEAM

Martin Langner, Georg-August-Universität Göttingen (University of Göttingen)

Ramin Yahyapour, Georg-August-Universität Göttingen (University of Göttingen)

Lucie Böttger, Georg-August-Universität Göttingen (University of Göttingen)

Alexander Zeckey, Georg-August-Universität Göttingen (University of Göttingen)

LINK

https://www.uni-goettingen.de/de/598167.html