Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project
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Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project Gabriele Gattiglia, Francesca Anichini, Holly Wright EAA Barcelona, September 6, 2018
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Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project
- 1. Gabriele Gattiglia1, Francesca Anichini1, Holly Wright2 1University of Pisa, 2University of York EAA Barcelona, September 6, 2018| Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project
- 2. Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE projectPartners University of Pisa (coordinator) Dipartimento di Civiltà e forme del sapere CNR –Istituto di Scienza e Tecnologie dell’Informazione INERA srl University of Barcelona Fac. de Prehistòria, Història Antiga i Arquelogia BARAKA ELEMENTS University of York Archaeology Data Service University of Cologne Institut für Archäologie University of Tel Aviv School of Computer Science An EC H2020 project Call Reflective 6, RIA (Research and Innovation Action) Duration: 36 months Project Started on June 1st, 2016 and end on May 31st 2019
- 3. ArchAIDE aims to support the classification and interpretation work of the archaeologists with innovative computer-based tools, able to provide the user with features for matching of each discovered sherd over the huge existing ceramic catalogues. from to Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project
- 4. recognition requires: • complex skills and since it is heavily dependent on human inspection and interpretation it is a very time consuming activity; • a boundless bibliography, fragmented and incoherent, whose consultation is long and fatiguing also when is available a well furnished library … Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project We want to innovate the archaeological practice, introducing a modern computer-aided approach but we want to keep as much as possible unchanged the overall methodology, to ensure easy adaptation and impact in the archaeology domain.
- 5. Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project
- 6. Roman Amphorae Terra Sigillata Maiolica Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project
- 7. [Database]
- 8. Database Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project
- 10. Appearancebasedrecognition 1 3 Ranking of pottery classes by relevance 2 Shapebasedrecognition Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project
- 12. ArchAIDE Archaeological Automatic Interpretation and Documentation of cEramics
- 13. ArchAIDE Archaeological Automatic Interpretation and Documentation of cEramics
- 14. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N.693548 The views and opinions expressed in this presentation are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. [Thank you for your attention] www.archaide.eu
- 15. Navigating a new digital interface: using automated image recognition to identify pottery in the ArchAIDE project We are at stand 43 (in the courtyard)
Notas do Editor
- One of the main goals of ArchAIDE project is to support the work of archaeologists towards an automatic classification (and description) of pottery sherds. This can be reached by taking into account the features that archaeologists compare in order to assign a sherd to a typology. While some of them are hard to be inserted in an automatic system (due to the necessary background and high-level reasoning of archaeologists), there are two descriptors that could be used: shape and appearance. Both of them are used on field, with a different degree of importance w.r.t. different classes of ceramic. Shape and appearance information has been structured in a number of catalogues, which are the main reference during the classification process. From the technical point of view, there are two main aspects that have to be taken into account: • The information that will be extracted from the catalogues (mainly from the reference drawings, but possibly also from the text) has to be extracted also from the images acquired on-site. Hence, it’s necessary to select a proper set of features, and also to provide guidelines for the acquisition of images when excavating. • The classification will be performed by an automatic system that has to be “trained” using real or synthetic data. Hence it is necessary to be able to provide enough input data so that the system is able to learn how to classify in a robust way.
- Any questions?