The goal of these two case-studies is not only to develop procedures for automatically generating corpora using image and 3D pattern recognition, but also to reflect on the associated schematisations and how they can be applied in computer science and visual sciences. Based on 200 terracottas of the late 4th and 3rd centuries BC, which are quite similar to each other, a classification system will be elaborated with digital methods, which is able to meet the complexity of the artefacts. For this purpose, methods of object-mining in 3D data are to be developed, which support the search for a suitable classification and categorisation of the images. The same holds true for a corpus of 80,000 Athenian Vase-Paintings, which are examined in relation to composition and content. A newly set up project is also trying to automatically attribute a vase to a certain painter. In close cooperation between computer science and archaeology, these experimental processes thus lead to a fundamental examination of the concept of pattern recognition as a humanities category. For the question of the relevance of the similarity networks for concrete relationships between the figurines or vases, the use of computers can also provide impulses because it is possible to describe the type and degree of similarity in a comprehensible way. A further goal is to test digital image classification methods by fundamentally investigating the relationship between archaeological hermeneutics, intuitive connoisseurship and data-based objectification of cognition in a central and intensively researched area of Classical Archaeology.
Author(s): Langner, Martin - Zeckey, Alexander (Georg-August-Universität Göttingen)
