4 research outputs found
ArchAIDE-Archaeological Automatic Interpretation and Documentation of cEramics
The goals of H2020 project "ArchAIDE: are to support the classification and interpretation work of archaeologists with innovative computer-based tools, able to provide the user with features for the semi-automatic description and matching of potsherds over the huge existing ceramic catalogues. Pottery classification is of fundamental importance for the comprehension and dating of the archaeological contexts, and for understanding production, trade flows and social interactions, but it requires complex skills and it is a very time consuming activity, both for researchers and professionals. The aim of ArchAIDE is to support the work of archaeologists, in order to meet real user needs and generate economic benefits, reducing time and costs. This would create societal benefits from cultural heritage, improving access, re-use and exploitation of the digital cultural heritage in a sustainable way. These objectives will be achieved through the development of: - an as-automatic-as-possible procedure to transform the paper catalogues in a digital description, to be used as a data pool for search and retrieval process; - a tool (mainly designed for mobile devices) that will support archaeologists in recognizing and classifying potsherds during excavation and post-excavation analysis, through an easy-to-use interface and efficient algorithms for characterisation, search and retrieval of the visual/geometrical correspondences; - an automatic procedure to derive a complete potsherds identity card by transforming the data collected into a formatted electronic document, printable or visual; - a web-based real-time data visualisation to improve access to archaeological heritage and generate new understanding; - an open archive to allow the archival and re-use of archaeological data, transforming them into common heritage and permitting economic sustainability. Those tools will be tested and assessed on real-cases scenarios, paving the way to future exploitation
Developing the ArchAIDE Application: A digital workflow for identifying, organising and sharing archaeological pottery using automated image recognition
Pottery is of fundamental importance for understanding archaeological contexts, facilitating the understanding of production, trade flows, and social interactions. Pottery characterisation and the classification of ceramics is still a manual process, reliant on analogue catalogues created by specialists, held in archives and libraries. The ArchAIDE project worked to streamline, optimise and economise the mundane aspects of these processes, using the latest automatic image recognition technology, while retaining key decision points necessary to create trusted results. Specifically, ArchAIDE worked to support classification and interpretation work (during both fieldwork and post-excavation analysis) with an innovative app for tablets and smartphones. This article summarises the work of this three-year project, funded by the European Union's Horizon 2020 Research and Innovation Programme under grant agreement N.693548, with a consortium of partners representing both the academic and industry-led ICT (Information and Communications Technology) domains, and the academic and development-led archaeology domains. The collaborative work of the archaeological and technical partners created a pipeline where potsherds are photographed, their characteristics compared against a trained neural network, and the results returned with suggested matches from a comparative collection with typical pottery types and characteristics. Once the correct type is identified, all relevant information for that type is linked to the new sherd and stored within a database that can be shared online. ArchAIDE integrated a variety of novel and best-practice approaches, both in the creation of the app, and the communication of the project to a range of stakeholders
Developing the ArchAIDE application: A digital workflow for identifying, organising and sharing archaeological pottery using automated image recognition
Every day, archaeologists are working to discover and tell stories using objects from the past, investing considerable time, effort and funding to identify and characterise individual finds. Pottery is of fundamental importance for the comprehension and dating of archaeological contexts, and for understanding the dynamics of production, trade flows, and social interactions. Today, characterisation and classification of ceramics are carried out manually, through the expertise of specialists and the use of analogue catalogues held in archives and libraries. While not seeking to replace the knowledge and expertise of specialists, the ArchAIDE project (archaide.eu) worked to optimise and economise identification process, developing a new system that streamlines the practice of pottery recognition in archaeology, using the latest automatic image recognition technology. At the same time, ArchAIDE worked to ensure archaeologists remained at the heart of the decision-making process within the identification workflow, and focussed on optimising tasks that were repetitive and time consuming. Specifically, ArchAIDE worked to support the essential classification and interpretation work of archaeologists (during both fieldwork and post-excavation analysis) with an innovative app for tablets and smartphones. This paper summarises the work of this three-year project, funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement N.693548, with a consortium of partners which has representing both the academic and industry-led ICT domains, and the academic and development-led archaeology domains. The collaborative work of the archaeological and technical partners created a pipeline where potsherds are photographed, their characteristics compared against a trained neural network, and the results returned with suggested matches from a comparative collection with typical pottery types and characteristics. Once the correct type is identified, all relevant information for that type is linked to the new sherd and stored within a database that can be shared online