With the increasing use of a range of advanced technical imaging and spectroscopic imaging methods in the study and preservation of artworks and other cultural heritage artefacts, there is growing interest in and need for computational approaches to fully realise the potential in the data acquired, to automate aspects of the processing and interpretation of the data and to be able to address research questions in a variety of disciplines. This is a rapidly growing field of research that is only possible through cross-disciplinary collaboration.

The aim of this conference is to provide a forum to bring together a multi-disciplinary and international group of researchers and professionals working in cultural heritage organisations including:

• scientists and conservators working with various forms of technical imaging or spectroscopic imaging on paintings and other cultural heritage artefacts in museums, galleries and universities

• researchers working in computer science, data science, computational image processing, computer vision, machine learning and AI, mathematics and statistics

• art historians, archaeologists and curators with an interest in the possibilities of technical imaging and/or those working in the digital humanities

to share their research and find fertile areas of collaboration and common inquiry.

The conference is being organised as part of the EPSRC-funded ARTICT | Art Through the ICT Lens: Big Data Processing Tools to Support the Technical Study, Preservation and Conservation of Old Master Paintings project (a collaboration between the National Gallery, University College London and Imperial College London) and builds on the success of the Image processing for art investigation (IP4AI) workshops, first established in 2007. The aim of IP4AI is to support art scholarship with new computational tools that enable new findings, and this conference aims to expand the original IP4AI remit to include both image and signal processing approaches as applied to the investigation of artworks and other cultural heritage artefacts.

Computational approaches for technical imaging in cultural heritage