ARTICT | Art Through the ICT Lens: Big Data Processing Tools to Support the Technical Study, Preservation and Conservation of Old Master Paintings
Lead Research Organisation:
University College London
Department Name: Electronic and Electrical Engineering
Abstract
The heritage science sector is experiencing a digital revolution linked to the emergence and increasing adoption of cutting-edge non-invasive analytical imaging techniques generating large volumes of multidimensional data from cultural heritage objects. These include macro X-Ray fluorescence (MA-XRF) scanning and hyperspectral imaging (HSI). Combining MA-XRF and HSI data - providing elemental and molecular information - offers huge potential for improved identification, characterization, and visualisation of the materials and features of interest in a painting, including in sub-surface layers of the painting. However, it is increasingly recognised that the wealth of data associated with these modalities cannot be fully exploited through traditional primarily manual approaches to interrogating heritage science data.
The aim of this research - bringing together ICT and Heritage Science researchers to enable the cross-pollination of ideas and expertise - is to co-create new automatic signal analysis and processing tools that are able to 'fuse' MA-XRF and HSI data to support the technical study, conservation and preservation artwork.
In particular, the proposed tools will provide the means to identify, characterize and visualize materials present within a painting, thereby leading to new insights relevant for the conservation and preservation of Old Master paintings or to new ways to engage the public with cultural heritage, science and ICT. For example, the proposed tools will also help visualise in a more integrated and accessible form the features of interest for art-historical study and conservation, such as underdrawing, pentimenti, concealed designs, losses or non-original materials.
To develop such tools, an ambitious research programme is proposed that includes development of: 1) multidimensional multimodal heritage science datasets, 2) multimodal signal processing algorithms for data correction, alignment, registration and mosaicking; and 3) new multimodal signal analysis algorithms capable of inferring material distributions in a painting from MA-XRF and HSI data. In addition, this research programme also envisions a number of significant advances in the area of signal processing - including new sparsity-driven nonlinear unmixing algorithms - that address the specific challenges arising in art investigation that do not arise in other application domains of signal processing, such as the need to identity mixtures of (aged) materials in superimposed layers using combined MA-XRF and HSI datasets.
The research programme also includes a number of case studies on National Gallery paintings that will assess the validity, potential and relevance of the proposed tools to the wider heritage sector.
The other aim of this research is to champion and sustain co-creation activities across the ICT and Heritage Science sectors. The activities planned during and beyond the project include: a) training of researchers, doctoral students, and undergraduate students; b) dedicated courses, workshops and events; c) outreach and public engagement activities; and d) a UK-wide network in the area of "ICT for Art Investigation". These aim to augment the project's co-creation and cross-disciplinary ethos and catalyse further research.
The ideas and tools conceived throughout the research will lead to impact across various levels and communities: a) the ICT sector will be exposed to new challenges stimulating developments in a new area of signal processing for art investigation; b) the Heritage Science sector will benefit from new automated, accessible, robust, user-friendly tools to aid the work of heritage scientists, art historians, and conservators. Finally, the tools and the images and insights they create will provide galleries with new innovative means to interpret and present their collections to the general public.
The aim of this research - bringing together ICT and Heritage Science researchers to enable the cross-pollination of ideas and expertise - is to co-create new automatic signal analysis and processing tools that are able to 'fuse' MA-XRF and HSI data to support the technical study, conservation and preservation artwork.
In particular, the proposed tools will provide the means to identify, characterize and visualize materials present within a painting, thereby leading to new insights relevant for the conservation and preservation of Old Master paintings or to new ways to engage the public with cultural heritage, science and ICT. For example, the proposed tools will also help visualise in a more integrated and accessible form the features of interest for art-historical study and conservation, such as underdrawing, pentimenti, concealed designs, losses or non-original materials.
To develop such tools, an ambitious research programme is proposed that includes development of: 1) multidimensional multimodal heritage science datasets, 2) multimodal signal processing algorithms for data correction, alignment, registration and mosaicking; and 3) new multimodal signal analysis algorithms capable of inferring material distributions in a painting from MA-XRF and HSI data. In addition, this research programme also envisions a number of significant advances in the area of signal processing - including new sparsity-driven nonlinear unmixing algorithms - that address the specific challenges arising in art investigation that do not arise in other application domains of signal processing, such as the need to identity mixtures of (aged) materials in superimposed layers using combined MA-XRF and HSI datasets.
The research programme also includes a number of case studies on National Gallery paintings that will assess the validity, potential and relevance of the proposed tools to the wider heritage sector.
The other aim of this research is to champion and sustain co-creation activities across the ICT and Heritage Science sectors. The activities planned during and beyond the project include: a) training of researchers, doctoral students, and undergraduate students; b) dedicated courses, workshops and events; c) outreach and public engagement activities; and d) a UK-wide network in the area of "ICT for Art Investigation". These aim to augment the project's co-creation and cross-disciplinary ethos and catalyse further research.
The ideas and tools conceived throughout the research will lead to impact across various levels and communities: a) the ICT sector will be exposed to new challenges stimulating developments in a new area of signal processing for art investigation; b) the Heritage Science sector will benefit from new automated, accessible, robust, user-friendly tools to aid the work of heritage scientists, art historians, and conservators. Finally, the tools and the images and insights they create will provide galleries with new innovative means to interpret and present their collections to the general public.
Planned Impact
Heritage science plays a key role in promoting access to cultural heritage, its interpretation, conservation and management, and this research will offer a range of new multimodal, multidimensional data analysis and processing tools with potential to lead to direct impact on this sector. Further, in view of culture's importance to UK life and tourism, the research will have indirect impact on the UK's economy and society.
Of particular relevance is the current interest in the cultural heritage sector - stimulated by the emergence of new non-invasive imaging techniques and a desire to minimise removal of physical samples for analysis - in the development of automated data processing/analysis tools to support the technical study, preservation and conservation of artworks. The immediate impact of this research on the activities of the National Gallery (NG) or other cultural heritage institutions in the UK and overseas will be as follows:
1 The proposed tools will enhance the ability of heritage scientists and art historians to study aspects of an artwork's creation, including the artist's palette, materials and technique, the artwork's provenance, or changing appearance over time, influencing how artworks are interpreted and presented.
2 The proposed tools will also enhance the understanding of heritage scientists and conservators of an artwork's conservation history, e.g. characterising non-original materials, areas of damage, etc., impacting on conservation approaches to unique (national) collections.
3 The availability of multimodal data analysis technology offers heritage scientists the means to readily combine, interpret, and re-interrogate the existing and expanding datasets that many cultural heritage institutions hold for their collections, maximising the potential of such bodies of data and the understanding of the associated artworks. Further, the tools also offer the potential to make complex scientific data more accessible by presenting a combined interpretation based on data from multiple modalities in a single image.
The visual outputs from the tools - and insights they will create - also provide innovative new ways to present paintings or other artworks within the cultural heritage sector (e.g. art historians&conservators) and to a wider audience. Via presentation on modern digital devices this could range from new views about an artwork's creation and conservation history to new ways to interact digitally with artwork using augmented reality technology that could be the basis for new exhibitions in museums or galleries. The NG's experience with exhibitions and web features based on technical examination of paintings suggests this highly visual area of applied science is an effective way to engage with the public and can increase public understanding of science and ICT.
The research will also promote new avenues of enquiry in the area of signal processing - notably, "Signal Processing for Art Investigation" - as well as a co-creation and cross-disciplinary culture within the wider area of "ICT for Art Investigation". It is anticipated that by demonstrating the power of ICT and signal processing research to solve real challenges in another sector, this project will influence both new research directions within the ICT community along with further co-created, cross-disciplinary ICT research in the cultural heritage sector, and within the Arts&Humanities more generally.
The reputations of the applicant organisations in their respective communities, and their wide international academic and professional networks, will ensure the impact of this research within the ICT sector, the Heritage Science sectors and with heritage end-users. Of particular relevance here is the NG's involvement in developing the European Research Infrastructure on Heritage Science (E-RIHS, www.e-rihs.eu). The experience of the applicants in public engagement activities will ensure the wider impact of the research is realised
Of particular relevance is the current interest in the cultural heritage sector - stimulated by the emergence of new non-invasive imaging techniques and a desire to minimise removal of physical samples for analysis - in the development of automated data processing/analysis tools to support the technical study, preservation and conservation of artworks. The immediate impact of this research on the activities of the National Gallery (NG) or other cultural heritage institutions in the UK and overseas will be as follows:
1 The proposed tools will enhance the ability of heritage scientists and art historians to study aspects of an artwork's creation, including the artist's palette, materials and technique, the artwork's provenance, or changing appearance over time, influencing how artworks are interpreted and presented.
2 The proposed tools will also enhance the understanding of heritage scientists and conservators of an artwork's conservation history, e.g. characterising non-original materials, areas of damage, etc., impacting on conservation approaches to unique (national) collections.
3 The availability of multimodal data analysis technology offers heritage scientists the means to readily combine, interpret, and re-interrogate the existing and expanding datasets that many cultural heritage institutions hold for their collections, maximising the potential of such bodies of data and the understanding of the associated artworks. Further, the tools also offer the potential to make complex scientific data more accessible by presenting a combined interpretation based on data from multiple modalities in a single image.
The visual outputs from the tools - and insights they will create - also provide innovative new ways to present paintings or other artworks within the cultural heritage sector (e.g. art historians&conservators) and to a wider audience. Via presentation on modern digital devices this could range from new views about an artwork's creation and conservation history to new ways to interact digitally with artwork using augmented reality technology that could be the basis for new exhibitions in museums or galleries. The NG's experience with exhibitions and web features based on technical examination of paintings suggests this highly visual area of applied science is an effective way to engage with the public and can increase public understanding of science and ICT.
The research will also promote new avenues of enquiry in the area of signal processing - notably, "Signal Processing for Art Investigation" - as well as a co-creation and cross-disciplinary culture within the wider area of "ICT for Art Investigation". It is anticipated that by demonstrating the power of ICT and signal processing research to solve real challenges in another sector, this project will influence both new research directions within the ICT community along with further co-created, cross-disciplinary ICT research in the cultural heritage sector, and within the Arts&Humanities more generally.
The reputations of the applicant organisations in their respective communities, and their wide international academic and professional networks, will ensure the impact of this research within the ICT sector, the Heritage Science sectors and with heritage end-users. Of particular relevance here is the NG's involvement in developing the European Research Infrastructure on Heritage Science (E-RIHS, www.e-rihs.eu). The experience of the applicants in public engagement activities will ensure the wider impact of the research is realised
Publications
Sabetsarvestani Z
(2019)
Artificial intelligence for art investigation: Meeting the challenge of separating x-ray images of the Ghent Altarpiece.
in Science advances
Sabetsarvestani Z
(2020)
Source Separation With Side Information Based on Gaussian Mixture Models With Application in Art Investigation
in IEEE Transactions on Signal Processing
Jill Dunkerton
(2020)
A Case of Collaboration: The Adoration of the Kings by Botticelli and Filippino Lippi Part II: Investigating the Collaboration
in National Gallery Technical Bulletin
Zhou C
(2021)
An ADMM Based Network for Hyperspectral Unmixing Tasks
Yan S
(2021)
When de Prony Met Leonardo: An Automatic Algorithm for Chemical Element Extraction From Macro X-Ray Fluorescence Data
in IEEE Transactions on Computational Imaging
Pu W
(2022)
Mixed X-Ray Image Separation for Artworks With Concealed Designs.
in IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Huang JJ
(2022)
WINNet: Wavelet-Inspired Invertible Network for Image Denoising.
in IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Sober B
(2022)
Revealing and Reconstructing Hidden or Lost Features in Art Investigation
in IEEE BITS the Information Theory Magazine
Zhou C
(2022)
ADMM-Based Hyperspectral Unmixing Networks for Abundance and Endmember Estimation
in IEEE Transactions on Geoscience and Remote Sensing
Pu W
(2023)
Image Separation With Side Information: A Connected Auto-Encoders Based Approach
in IEEE Transactions on Image Processing
Yan S
(2023)
A Fast Automatic Method for Deconvoluting Macro X-Ray Fluorescence Data Collected From Easel Paintings
in IEEE Transactions on Computational Imaging
Zhou C
(2023)
Hyperspectral Blind Unmixing Using a Double Deep Image Prior.
in IEEE transactions on neural networks and learning systems
| Description | The team has developed a range of novel automated data processing algorithms capable of handling the complex multidimensional data modalities increasingly being acquired from paintings, including macro X-Ray Fluorescence (MA-XRF) scanning and hyperspectral imaging (HSI) datasets as well as visible images, X-radiographs and infrared reflectograms. These have been developed to address a range of real-world challenges presented by heritage users. These new data processing algorithms can offer key insights during technical investigation of paintings, including helping to identify, characterize and visualize materials present within a work. The research has also explored a number of approaches to improving the visualisation of features of interest, including those not visible at the surface of the painting such as underdrawing, adjustments to the composition, concealed designs, losses or non-original materials present within the stratigraphy. Such insights are important in helping to understand an artist's technique and how a given composition was developed or other changes that have occurred during the lifetime of a given work. Beyond the algorithm development to tackle particular case studies, effort has also been focused on developing user interfaces for a number of the methods and on exploring the 'generalisation' of the approaches in order to provide tools for use within the heritage sector. |
| Exploitation Route | (1) Art historians can use our results and encourage the use of our approaches in order to inform art-historical investigation. (2) Art conservators can use these results and encourage the use of our approaches in order to inform how to better conserve and preserve paintings. (3) New approaches and tools will be available to allow museum professionals to more effectively and efficiently interrogate new and existing data acquired from artworks, including the development of GUI to make user-friendly tools (4) By making the algorithms and underlying code available via Github, the approaches can also be developed by other ICT researchers in new applications and will help increase awareness in the ICT sector of the particularly challenging questions arising from data from art work and the heritage sector. |
| Sectors | Digital/Communication/Information Technologies (including Software),Culture, Heritage, Museums and Collections |
| URL | https://art-ict.github.io/artict/ |
| Description | Our data processing algorithms are currently being assessed and trialed by cultural heritage institutions in order to reveal key insights about paintings and improve efficiency and quality of data processing and interpretation. The algorithms developed have been used on data and images acquired from paintings at the National Gallery, London and are helping to improve the interpretation of their data and their data acquisition and processing workflows. This in turn is both relevant for the conservation and preservation of the Gallery's collection and is starting to feed into the Gallery's public and scholarly outputs including scholarly and exhibition catalogues and online content, offering new ways to interpret, share and present the collection. The algorithms are also being trialed on data from the National Gallery of Art, Washington, DC, and the Ghent Altarpiece Team as well as from the Fitzwilliam Museum, Cambridge. Dissemination efforts have been deliberately targeted at both the ICT and heritage sector to try and maximise impact. Some of these results have been recently reported in high-profile publications and the media worldwide. The work of this project is contributing to the growing interest within both the ICT and heritage sector in computational imaging for cultural heritage and the role of signal and image processing for art investigation. This helps to contribute to the increasing presence of the UK in this growing field of research. The importance of computational imaging is also being recognized within heritage institutions e.g. within the National Gallery's own research strategy and in a number of UKRI funding programmes supporting such institutions. |
| First Year Of Impact | 2019 |
| Sector | Culture, Heritage, Museums and Collections |
| Impact Types | Cultural |
| Description | Multi-Modal Signal Processing for Art Investigation |
| Amount | £90,750 (GBP) |
| Funding ID | NIF\R1\192656 |
| Organisation | The Royal Society |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 03/2019 |
| End | 02/2021 |
| Description | Multimodal analytical imaging of Old Master Paintings: addressing the challenges of registration, mosaic construction and image resolution |
| Amount | £79,800 (GBP) |
| Funding ID | AH/T002417/1 |
| Organisation | Arts & Humanities Research Council (AHRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 10/2020 |
| End | 03/2024 |
| Description | Collaboration with Fitzwilliam Museum and Hamilton Kerr Institute, University of Cambridge and the National Gallery |
| Organisation | University of Cambridge |
| Department | The Fitzwilliam Museum |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | With the recent acquisition of MA-XRF scanning equipment by the Fitzwilliam Museum, and the move of a number of members or partners of the ARTICT team to positions within the University of Cambridge, the long-standing links between the National Gallery and the Fitzwilliam Museum and Hamilton Kerr Institute, University of Cambridge have been strengthened over the last year. Sharing of expertise, datasets and comparative material relating to Old Master paintings, identification of common areas of interest as well as access to data and algorithms developed within the ARTICT project |
| Collaborator Contribution | Sharing of expertise, datasets and comparative material relating to Old Master paintings, identification of common areas of interest as well as access to data sets against which approaches developed within the ARTICT project can be tested |
| Impact | An online resource for the public (https://miniatures.fitz.ms/) is also being developed using one of the algorithms developing out of the ARTICT project which allows automated registration on multimodal imaging data from English Portrait Miniatures. The algorithm is facilitating registration of many image modalities for generating a curtain viewer for many of the objects in the online resource and the website should be launched fully by Autumn 2023. An AHRC funded collaborative doctoral partnership PhD studentship has also been secured (to start September 2023) entitled 'Re-evaluating punchmarks on Early Italian Paintings'. The academic supervisors will be based in the History of Art Department at the University of Cambridge and the non-HEI supervisor will be based in the Scientific Department of the National Gallery in London. The collaboration is multi-disciplinary involving heritage scientists, conservators and art historians and may in future also include input from mathematicians |
| Start Year | 2022 |
| Description | Collaboration with The Hebrew University of Jerusalem |
| Organisation | Hebrew University of Jerusalem |
| Country | Israel |
| Sector | Academic/University |
| PI Contribution | This research collaboration involved the development of new multi-modal data processing schemes with applications to art investigation. Our teams have contributed with the development/testing of algorithms and support of Dr Sober in applications to secure funding in his new position. |
| Collaborator Contribution | This research collaboration involved the development of new multi-modal data processing schemes with applications to art investigation. Our partner has contributed with insights and input from students based at the university. The ARTICT team were already collaborating with Dr Barak Sober when he was based at Duke University and this collaboration has continued with Dr Sober's move to the Hebrew University of Jerusalem |
| Impact | New collaboration but a number of articles and joint presentations have arisen and are detailed in the appropriate sections |
| Start Year | 2021 |
| Description | UCL / Duke Univ / National Gallery Collaboration |
| Organisation | Duke University |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | This research collaboration involved the development of new multi-modal data processing schemes with applications to art investigation. Our teams have contributed with the development/test of algorithms. |
| Collaborator Contribution | This research collaboration involved the development of new multi-modal data processing schemes with applications to art investigation. Our partner has contributed with intellectual insights, datasets, and dedicated students. |
| Impact | This collaboration has led to the publications: -- W. Pu, B. Sober, N. Daly, C. Higgitt, I. Daubechies, M. R. D. Rodrigues. A connected auto-encoders based approach for image separation with side information: with applications to art investigation. IEEE International Conference on Acoustics, Speech and Signal Processing, Barcelona, Spain, 2020. -- Z. Sabetsarvestani, B. Sober, C. Higgitt, I. Daubechies, M. R. D. Rodrigues, Artificial intelligence for art investigation: Meeting the challenge of separating x-ray images of the Ghent Altarpiece. Sci. Adv. 5, eaaw7416 (2019). |
| Start Year | 2018 |
| Description | 8 June 2020 - Presentation at CogX 2020 conference (London, but virtual) 'AI, heritage science and the technical examination of cultural heritage artefacts' |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Presentation entitled 'AI, heritage science and the technical examination of cultural heritage artefacts' given at the CogX 2020 conference on the Research - The Long View stage in the Alan Turing Institute: Artificial Intelligence in the Arts and Humanities session which was open to all CogX attendees and also recorded for open access viewing after the event |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://www.youtube.com/watch?v=FnFf3ltEHho |
| Description | ARTICT Project Website |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | We have launched a website reporting on the advances spear-headed within this project. |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://art-ict.github.io/artict/index.html |
| Description | ARTICT project website |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Project website created to share information about the project and project team, showcase a series of case studies, provide information about publications and presentations and to host information about the forthcoming conference (April 2022). The website is hosted on GitHub and will allow datasets and tools developed within the project to be shared once they are ready |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://art-ict.github.io/artict/home.html |
| Description | CogX 2019 Talk on "Artificial Intelligence for Art Investigation" |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | CogX 2019 Talk on "Artificial Intelligence for Art Investigation" |
| Year(s) Of Engagement Activity | 2019 |
| Description | Computational Imaging for Art Investigation: Revealing Hidden Drawings in Leonardo's Painting (Video Lecture) |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Webinar for the Webinar Series called "Computational Imaging Webinar Series SPACE" organized by the IEEE Signal Processing Society |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://www.youtube.com/watch?v=A00cBPpSMgA |
| Description | Computational approaches for technical imaging in cultural heritage (7th IP4AI meeting), 27-29 April, 2022 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A virtual conference was 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 in partnership with Duke University) 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. 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 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 the conference was to provide a forum to bring together a multi-disciplinary group of researchers 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 attracted just over 300 registered participants and included three invited keynote speakers, eleven oral contributions, a panel discussion (The role of AI for art investigation) and two virtual poster sessions were organised (on Gather) at which 20 posters were 'presented' and two software demonstrations undertaken |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://art-ict.github.io/artict/Conference.html |
| Description | Contribution to video produced by EPSRC (hosted on EPSRC website) to discuss cross-disciplinarity and co-creation in research |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Contribution to video produced by EPSRC (hosted on EPSRC website) to discuss cross-disciplinarity and co-creation in research based on our experience in developing a successful grant proposal |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://epsrc.ukri.org/research/ourportfolio/themes/ict/introduction/crossictpriorities/crossdiscipl... |
| Description | Fitzwilliam Museum 2019 Talk on "ARTICT: Art Through the ICT Lens" |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Fitzwilliam Museum Talk on "ARTICT: Art Through the ICT Lens" |
| Year(s) Of Engagement Activity | 2019 |
| Description | Imperial College Press Relerase and YouTube video |
| Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Media (as a channel to the public) |
| Results and Impact | The press release described research conducted by Imperial College and National Gallery teams that helped reveal under-drawing in the Leonardo da Vinci's painiting "Virgin of the Rocks". The press release is available here: https://www.imperial.ac.uk/news/195075/new-algorithm-helps-uncover-forgotten-figures/ The corresponding YouTube video with 72,000 views here: https://www.youtube.com/watch?v=oAmVLscVKqM&feature=youtu.be |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://www.imperial.ac.uk/news/195075/new-algorithm-helps-uncover-forgotten-figures/ |
| Description | International Congress on Industrial and Applied Mathematics 2019 Talk on "Artificial Intelligence for Art Investigation" |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | International Congress on Industrial and Applied Mathematics Talk on "Artificial Intelligence for Art Investigation" |
| Year(s) Of Engagement Activity | 2019 |
| Description | Interview for BBC Culture |
| Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Miguel Rodrigues and Catherine Higgitt were interviewed for an online article - see Lawson-Tancred, Jo. 'The Hidden Images Found in Masterpieces'. BBC Culture, 29th June 2022. https://www.bbc.com/culture/article/20220628-the-lost-masterpieces-being-revealed. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://www.bbc.com/culture/article/20220628-the-lost-masterpieces-being-revealed |
| Description | Interview for Nature Index |
| Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Catherine Higgitt was interviewed for an article in Nature Index about novel applications of AI methods in unexpected sectors. See Eisenstein, Michael. 'AI and Robotics: Getting a Grip on Denizens of the Deep'. Nature 610, no. Nature Index 2022 AI and robotics (2022): S6-8. https://doi.org/10.1038/d41586-022-03209-2. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://doi.org/10.1038/d41586-022-03209-2 |
| Description | Made at UCL Open Dat Talk on "Artificial Intelligence for Art Investigation" |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Public/other audiences |
| Results and Impact | Made at UCL Open Dat Talk on "Artificial Intelligence for Art Investigation" |
| Year(s) Of Engagement Activity | 2019 |
| Description | Poster presentation at Computational approaches for technical imaging in cultural heritage (7th IP4AI meeting) conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A number of oral presentations were given at the conference organised in 27-29 April 2022 as part of the ARTICT project by members of the ARTICT team including the following: "Neural network-based classification of X-ray fluorescence spectra of artists' pigments: an approach leveraging a synthetic dataset created using the fundamental parameters method" Nathan S. Daly, Cerys Jones, Catherine Higgitt & Miguel R.D. Rodrigues |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://art-ict.github.io/artict/programme.html |
| Description | Poster presentation at Computational approaches for technical imaging in cultural heritage (7th IP4AI meeting) conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A number of poster presentations were given at the conference organised in 27-29 April 2022 as part of the ARTICT project by members of the ARTICT team including the following: "Multimodal Image Registration of Old Masters Paintings" Maria Eugenia Villafañe, Su Yan, Junjie Huang, Nathan Daly, Catherine Higgitt & Pier Luigi Dragotti |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://art-ict.github.io/artict/programme.html |
| Description | Poster presentation at the Computational approaches for technical imaging in cultural heritage (7th IP4AI meeting) conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A number of poster presentations were given at the conference organised in 27-29 April 2022 as part of the ARTICT project by members or partners of the ARTICT team including the following: "Enhancing Underdrawing Visualization using Adaptive and Localized Image Analysis of Reflectance Hyperspectral Imaging Data from a 15th Century Painting" Wallace Peaslee, Marta Melchiorre Di Crescenzo, Nathan Daly, Ingrid Daubechies, Shira Faigenbaum Golovin, Catherine Higgitt & Barak Sober |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://art-ict.github.io/artict/programme.html |
| Description | Poster presentation at the Computational approaches for technical imaging in cultural heritage (7th IP4AI meeting) conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A number of poster presentations were given at the conference organised in 27-29 April 2022 as part of the ARTICT project by members or partners of the ARTICT team including the following: "Mapping the Distribution of Pigments in Paintings Using Macro XRF Element Maps and the Least Squares Method" Hojung (Ashley) Kwon, Barak Sober & Ingrid Daubechies |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://art-ict.github.io/artict/programme.html |
| Description | Practical IIIF Seminar - Image Registration |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Nathan Daly (ARTICT post-doctoral fellow based at the National Gallery) gave a presentation at the Practical IIIF Seminar on Image Registration to provide an overview of the current approaches to the mosaicking and registration of images and spectroscopic imaging data at the Nationa Gallery which was very well received and has lead to further interesting discussions with others working in the field. A presentation was also given by a colleague in the Photography and Imaging department of the National Gallery at the same event |
| Year(s) Of Engagement Activity | 2021 |
| Description | Presentation at MA-XRF scanning in Conservation, Art and Archaeology conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A presentation of work undertaken within the ARTICT project was presented at a conference aimed at heritage scientists working in universities and cultural heritage institutions entitled 'MA-XRF scanning in Conservation, Art and Archaeology 2022' held in Delft, Netherlands on 26-27 September 2022. The paper was presented by Nathan Daly with Su Yan, Jun-Jie Huang, Pier Luigi Dragotti and Catherine Higgitt as co-authors. The presentation was entitled 'A novel signal processing approach to deconvolute MA-XRF scanning data: a comparison to existing methods' |
| Year(s) Of Engagement Activity | 2022 |
| Description | Presentation at the Computational approaches for technical imaging in cultural heritage (7th IP4AI meeting) conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A number of oral presentations were given at the conference organised in 27-29 April 2022 as part of the ARTICT project by members of the ARTICT team including the following: "Automatic Algorithms for Deconvoluting Macro X-ray Fluorescence Data" presented by Su Yan with Jun-Jie Huang, Herman Verinaz-Jadan, Nathan Daly, Catherine Higgitt & Pier Luigi Dragotti as co-authors |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://art-ict.github.io/artict/programme.html |
| Description | Presentation at the Computational approaches for technical imaging in cultural heritage (7th IP4AI meeting) conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A number of oral presentations were given at the conference organised in 27-29 April 2022 as part of the ARTICT project by members of the ARTICT team including the following: Marta Melchiorre Di Crescenzo, Sotiria Kogou, Luke Butler, Florence Liggins, Haida Liang and Catherine Higgitt, 'Application of a novel neural network approach to investigate the painting materials and technique in 'The Adoration of the Kings' by Sandro Botticelli and Filippino Lippi |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://art-ict.github.io/artict/programme.html |
| Description | Presentation to the National Gallery's Scientific Consultative Group |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Update on research presented at the 2021 annual National Scientific Consultative Group meeting to the Director of the Gallery, the Chair of the Board of Trustees, the Scientific Trustee and other consultative group members as well as staff from the National Gallery |
| Year(s) Of Engagement Activity | 2021 |
| Description | Presentation to the Scientific Advisory Board of E-RIHS (http://www.e-rihs.eu/) |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A description of the activities being undertaken within the ARTICT project was included as part of a presentation to the Scientific Advisory Board of E-RIHS (http://www.e-rihs.eu/) at a meeting held at the NG (13.9.2019) |
| Year(s) Of Engagement Activity | 2019 |
| Description | Software demonstration at the Computational approaches for technical imaging in cultural heritage (7th IP4AI meeting) conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Software developed by members or partners of the ARTICT team was demonstrated at the conference organised in 27-29 April 2022 as part of the ARTICT project - the session was entitled "Automatic Algorithms for Deconvoluting Macro X-ray Fluorescence Data - Software Demonstration" and was given by Su Yan. The work demonstrated also involved Frederick McCallum, Jun-Jie Huang, Herman Verinaz-Jadan, Nathan Daly, Catherine Higgitt & Pier Luigi Dragotti |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://art-ict.github.io/artict/programme.html |
| Description | Turing AI & Arts Interest Group Webminar on "Artificial Intelligence for Art Investigation, Conservation, and Presentation" |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Turing AI & Arts Interest Group Webminar on "Artificial Intelligence for Art Investigation, Conservation, and Presentation" |
| Year(s) Of Engagement Activity | 2020 |
| Description | University College London Press Release and Media Coverage |
| Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Media (as a channel to the public) |
| Results and Impact | The press release described research conducted by University College London and National Gallery teams that helped separate mixed x-rays associated with double-sided paintings. The press release is available here: https://www.ucl.ac.uk/news/2019/sep/ai-uncovers-new-details-about-old-master-paintings https://www.ucl.ac.uk/iccs/news/2019/sep/ai-uncovers-new-details-about-old-master-paintings Media coverage includes: https://www.telegraph.co.uk/science/2019/08/30/hidden-works-goya-van-gogh-van-eyck-could-discovered-using-artifical/ https://www.forbes.com/sites/simonchandler/2019/09/06/forget-the-future-ai-will-take-us-back-to-the-past/#1cc67ddd2d13 |
| Year(s) Of Engagement Activity | 2019 |
| URL | http://www.ucl.ac.uk/news/2019/sep/ai-uncovers-new-details-about-old-master-paintings |
| Description | Video lecture for the general public entitled: "When art meets science: The algorithms that revealed Leonardo's hidden drawings" |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | This was a video lecture broadcasted on youtube as part of the Science Breaks initiative. Science Breaks is a virtual event series showcasing the impact and relevance of Imperial's research and work taking place at the College. THe focus of the lecture was about describing the algorithm we developed, as part of the ARTICT project, which helped reveal hidden drawings in the Leonardo's "the Virgin of the Rocks" painting. |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://www.youtube.com/watch?v=4pKXXRWbOVI |