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Marc Walton

Also published under: M. Walton

Publications
17
Citations
110
Publications by Year
20152022
Co-Authors:
Show All Co-Authors (37)
Image of author Marc Walton

Marc Walton

Also published under: M. Walton

Affiliation

M+, Kowloon, Hong Kong

Publication Topics

Biography

Marc Walton received the Ph.D. degree in archaeological science from the University of Oxford, Oxford, U.K. He is currently the Head of Conservation and Research with M+ Museum for Visual Culture, Hong Kong. Prior to joining M+ in 2022, he was a Senior Scientist with the Northwestern University/Art Institute of Chicago Center for Scientific Studies in the Arts (NU-ACCESS), which he joined in 2013. At NU-ACCESS, he led numerous collaborative initiatives and research projects to investigate art objects. His research interests include elucidating the trade and manufacture of objects using the physical sciences, and on the development of the use of imaging technologies in the field of conservation science.(Based on document published on 8 August 2022).
Publications
17
Citations
110
Publications by Year
20152022
Co-Authors:
Show All Co-Authors (37)
Author's Published Works

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Image Processing Perspectives of X-Ray Fluorescence Data in Cultural Heritage Sciences

Henry Chopp;Alicia McGeachy;Matthias Alfeld;Oliver Cossairt;Marc Walton;Aggelos Katsaggelos

IEEE BITS the Information Theory Magazine
Year: 2022 | Volume: 2, Issue: 1 | Magazine Article |
Cited by: Papers (2)
X-ray fluorescence (XRF) analysis of art objects has rapidly gained popularity since the late 2000s due to its increased accessibility to scientists. This introduced an imaging component whereby the XRF image volume provides clues as to which chemical elements are present and where they are located spatially in the object. However, as is the nature of collecting measurements, there are limitations...Show More

Image Processing Perspectives of X-Ray Fluorescence Data in Cultural Heritage Sciences

Henry Chopp;Alicia McGeachy;Matthias Alfeld;Oliver Cossairt;Marc Walton;Aggelos Katsaggelos

Year: 2022 | Volume: 2, Issue: 1 | Magazine Article |

Skinscan: 3D Dermatologic Diagnosis and Documentation with Commodity Devices

Merlin A. Nau;Florian Schiffers;Yunhao Li;Bingjie Xu;Andreas Maier;Jack Tumblin;Marc Walton;Aggelos K. Katsaggelos;Florian Willomitzer;Oliver Cossairt

2021 55th Asilomar Conference on Signals, Systems, and Computers
Year: 2021 | Conference Paper |
Computational photography has become a valuable field of interest for dermatologists. Current telemedical approaches mainly use two-dimensional (2D) color imagery, which cannot always capture sufficient information for the physician. In clinical practice dedicated imaging systems can acquire valuable three-dimensional (3D) data to improve the patients outcome [1], [2]. The major drawback of clinic...Show More

Skinscan: 3D Dermatologic Diagnosis and Documentation with Commodity Devices

Merlin A. Nau;Florian Schiffers;Yunhao Li;Bingjie Xu;Andreas Maier;Jack Tumblin;Marc Walton;Aggelos K. Katsaggelos;Florian Willomitzer;Oliver Cossairt

Year: 2021 | Conference Paper |

Skinscan: Low-Cost 3D-Scanning for Dermatologic Diagnosis and Documentation

Merlin A. Nau;Florian Schiffers;Yunhao Li;Bingjie Xu;Andreas Maier;Jack Tumblin;Marc Walton;Aggelos K. Katsaggelos;Florian Willomitzer;Oliver Cossairt

2021 IEEE International Conference on Image Processing (ICIP)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
The utilization of computational photography becomes increasingly essential in the medical field. Today, imaging techniques for dermatology range from two-dimensional (2D) color imagery with a mobile device to professional clinical imaging systems measuring additional detailed three-dimensional (3D) data. The latter are commonly expensive and not accessible to a broad audience. In this work, we pr...Show More

Skinscan: Low-Cost 3D-Scanning for Dermatologic Diagnosis and Documentation

Merlin A. Nau;Florian Schiffers;Yunhao Li;Bingjie Xu;Andreas Maier;Jack Tumblin;Marc Walton;Aggelos K. Katsaggelos;Florian Willomitzer;Oliver Cossairt

Year: 2021 | Conference Paper |

A Data Fusion Method For The Delayering Of X-Ray Fluorescence Images Of Painted Works Of Art

L. D. Fiske;A. K. Katsaggelos;M. C. G. Aalders;M. Alfeld;M. Walton;O. Cossairt

2021 IEEE International Conference on Image Processing (ICIP)
Year: 2021 | Conference Paper |
Cited by: Papers (6)
In this manuscript, we address the problem of studying layer structure in X-ray Fluorescence (XRF) elemental maps of paintings through the incorporation of reflectance imaging spectral data in the visible or near IR range. We propose a conceptually flexible approach, which involves an initial clustering step for the visible hyperspectral reflectance data (RIS) and the formation of a synthetic surf...Show More

A Data Fusion Method For The Delayering Of X-Ray Fluorescence Images Of Painted Works Of Art

L. D. Fiske;A. K. Katsaggelos;M. C. G. Aalders;M. Alfeld;M. Walton;O. Cossairt

Year: 2021 | Conference Paper |

Low-budget 3D scanning and material estimation using PyTorch3D

Oliver Cossairt;Florian Willomitzer;Chai-Kai Yeh;Marc Walton

2020 54th Asilomar Conference on Signals, Systems, and Computers
Year: 2020 | Conference Paper |
Cited by: Papers (1)
In this paper, we present recent results on our effort to develop low-budget, high precision 3D scanning solutions for art museum conservators. There is a real need for this in cultural heritage applications where the potential to detect and monitor degradations is of critical importance, but financial resources for high-quality 3D scanning devices is limited to a select few larger institutions. T...Show More

Low-budget 3D scanning and material estimation using PyTorch3D

Oliver Cossairt;Florian Willomitzer;Chai-Kai Yeh;Marc Walton

Year: 2020 | Conference Paper |

Adaptive Image Sampling Using Deep Learning and Its Application on X-Ray Fluorescence Image Reconstruction

Qiqin Dai;Henry Chopp;Emeline Pouyet;Oliver Cossairt;Marc Walton;Aggelos K. Katsaggelos

IEEE Transactions on Multimedia
Year: 2020 | Volume: 22, Issue: 10 | Journal Article |
Cited by: Papers (25)
This paper presents an adaptive image sampling algorithm based on Deep Learning (DL). It consists of an adaptive sampling mask generation network which is jointly trained with an image inpainting network. The sampling rate is controlled by the mask generation network, and a binarization strategy is investigated to make the sampling mask binary. In addition to the image sampling and reconstruction ...Show More

Adaptive Image Sampling Using Deep Learning and Its Application on X-Ray Fluorescence Image Reconstruction

Qiqin Dai;Henry Chopp;Emeline Pouyet;Oliver Cossairt;Marc Walton;Aggelos K. Katsaggelos

Year: 2020 | Volume: 22, Issue: 10 | Journal Article |

3D Surface Measurement and Analysis of Works of Art

Bingjie Xu;Florian Willomitzer;Chia-Kai Yeh;Fengqiang Li;Vikas Gupta;Jack Tumblin;Marc Walton;Oliver Cossairt

2019 53rd Asilomar Conference on Signals, Systems, and Computers
Year: 2019 | Conference Paper |
Cited by: Papers (4)
Surface shape metrology encompasses broad topics within cultural heritage science. However, most existing surface shape measurement systems are bulky and restricted to lab environments. As most are not practical for large, delicate or fixed works of art, such as stained-glass windows or oil-painted murals, we develop methods to measure matte and specular surfaces using hand-held mobile devices. In...Show More

3D Surface Measurement and Analysis of Works of Art

Bingjie Xu;Florian Willomitzer;Chia-Kai Yeh;Fengqiang Li;Vikas Gupta;Jack Tumblin;Marc Walton;Oliver Cossairt

Year: 2019 | Conference Paper |

Pigment Unmixing of Hyperspectral Images of Paintings Using Deep Neural Networks

Neda Rohani;Emeline Pouyet;Marc Walton;Oliver Cossairt;Aggelos K. Katsaggelos

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2019 | Conference Paper |
Cited by: Papers (12)
In this paper, the problem of automatic nonlinear unmixing of hyperspectral reflectance data using works of art as test cases is described. We use a deep neural network to decompose a given spectrum quantitatively to the abundance values of pure pigments. We show that adding another step to identify the constituent pigments of a given spectrum leads to more accurate unmixing results. Towards this,...Show More

Pigment Unmixing of Hyperspectral Images of Paintings Using Deep Neural Networks

Neda Rohani;Emeline Pouyet;Marc Walton;Oliver Cossairt;Aggelos K. Katsaggelos

Year: 2019 | Conference Paper |

Shape-from-Shifting: Uncalibrated Photometric Stereo with a Mobile Device

Chia-Kai Yeh;Fengqiang Li;Gianluca Pastorelli;Marc Walton;Aggelos K. Katsaggelos;Oliver Cossairt

2017 IEEE 13th International Conference on e-Science (e-Science)
Year: 2017 | Conference Paper |
Cited by: Papers (2)
Surface shape scanning techniques, such as laser scanning and photometric stereo, are widespread analytical tools used in the field of cultural heritage. Compared to regular 2D RGB photos, 3D surface scans provide higher fidelity of an object's surface shape which assist conservators, art historians, and archaeologists in understanding how these artworks and artifacts are made and to digitally doc...Show More

Shape-from-Shifting: Uncalibrated Photometric Stereo with a Mobile Device

Chia-Kai Yeh;Fengqiang Li;Gianluca Pastorelli;Marc Walton;Aggelos K. Katsaggelos;Oliver Cossairt

Year: 2017 | Conference Paper |

Spatial-Spectral Representation for X-Ray Fluorescence Image Super-Resolution

Qiqin Dai;Emeline Pouyet;Oliver Cossairt;Marc Walton;Aggelos K. Katsaggelos

IEEE Transactions on Computational Imaging
Year: 2017 | Volume: 3, Issue: 3 | Journal Article |
Cited by: Papers (10)
X-ray fluorescence (XRF) scanning of works of art is becoming an increasing popular nondestructive analytical method. The high quality XRF spectra is necessary to obtain significant information on both major and minor elements used for characterization and provenance analysis. However, there is a tradeoff between the spatial resolution of an XRF scan and the signal-to-noise ratio (SNR) of each pix...Show More

Spatial-Spectral Representation for X-Ray Fluorescence Image Super-Resolution

Qiqin Dai;Emeline Pouyet;Oliver Cossairt;Marc Walton;Aggelos K. Katsaggelos

Year: 2017 | Volume: 3, Issue: 3 | Journal Article |

Automatic pigment identification on roman Egyptian paintings by using sparse modeling of hyperspectral images

Neda Rohani;Johanna Salvant;Sara Bahaadini;Oliver Cossairt;Marc Walton;Aggelos Katsaggelos

2016 24th European Signal Processing Conference (EUSIPCO)
Year: 2016 | Conference Paper |
Cited by: Papers (10)
In this paper, we study the problem of automatic identification of pigments applied to paintings using hyperspectral reflectance data. Here, we cast the problem of pigment identification in a novel way by decomposing the spectrum into pure pigments. The pure pigment exemplars, chosen and prepared in our laboratory based on historic sources and archaeological examples, closely resemble the material...Show More

Automatic pigment identification on roman Egyptian paintings by using sparse modeling of hyperspectral images

Neda Rohani;Johanna Salvant;Sara Bahaadini;Oliver Cossairt;Marc Walton;Aggelos Katsaggelos

Year: 2016 | Conference Paper |

Computational Imaging for Cultural Heritage: Recent developments in spectral imaging, 3-D surface measurement, image relighting, and X-ray mapping

Xiang Huang;Erich Uffelman;Oliver Cossairt;Marc Walton;Aggelos K. Katsaggelos

IEEE Signal Processing Magazine
Year: 2016 | Volume: 33, Issue: 5 | Magazine Article |
Cited by: Papers (18)
Because art is inherently visual, the use of imaging has long been an important way to understand its structure, form, and history. Recently, new ways of engaging with objects from our shared cultural heritage are possible with advances in computation and imaging that allow scientists to analyze art noninvasively, historians to pose new social questions about the art, and the public to explore and...Show More

Computational Imaging for Cultural Heritage: Recent developments in spectral imaging, 3-D surface measurement, image relighting, and X-ray mapping

Xiang Huang;Erich Uffelman;Oliver Cossairt;Marc Walton;Aggelos K. Katsaggelos

Year: 2016 | Volume: 33, Issue: 5 | Magazine Article |

X-Ray fluorescence image super-resolution using dictionary learning

Qiqin Dai;Emeline Pouyet;Oliver Cossairt;Marc Walton;Francesca Casadio;Aggelos Katsaggelos

2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP)
Year: 2016 | Conference Paper |
Cited by: Papers (4)
X-Ray fluorescence (XRF) scanning of works of art is becoming an increasingly popular non-destructive analytical method. The high quality XRF spectra is necessary to obtain significant information on both major and minor elements used for characterization and provenance analysis. However, there is a trade-off between the spatial resolution of an XRF scan and the Signal-to-Noise Ratio (SNR) of each...Show More

X-Ray fluorescence image super-resolution using dictionary learning

Qiqin Dai;Emeline Pouyet;Oliver Cossairt;Marc Walton;Francesca Casadio;Aggelos Katsaggelos

Year: 2016 | Conference Paper |

Keynote speakers: Computational imaging: How much imaging — How much computation?

Gerd Häusler;David Forsyth;Marc Walton;Francis Halzen;Aydogan Ozcan

2016 IEEE International Conference on Computational Photography (ICCP)
Year: 2016 | Conference Paper |
This talk will discuss (from the viewpoint of a physicist with background in optical engineering and information) how much imaging and how much computing is (or should be) in computational imaging, aiming for high information efficiency. For an opticist the order of the keywords “computational imaging” is inverted: imaging is the first operation in the sequence, as optics does the encoding for red...Show More

Keynote speakers: Computational imaging: How much imaging — How much computation?

Gerd Häusler;David Forsyth;Marc Walton;Francis Halzen;Aydogan Ozcan

Year: 2016 | Conference Paper |

Surface shape studies of the art of Paul Gauguin

Oliver Cossairt;Xiang Huang;Nathan Matsuda;Harriet Stratis;Mary Broadway;Jack Tumblin;Greg Bearman;Eric Doehne;Aggelos Katsaggelos;Marc Walton

2015 Digital Heritage
Year: 2015 | Conference Paper |
Cited by: Papers (2)
Starting in the 1890s the artist Paul Gauguin (1848-1903) created a series of prints and transfer drawings using techniques that are not entirely understood. To better understand the artist's production methods, photometric stereo was used to assess the surface shape of a number of these graphic works that are now in the collection of the Art Institute of Chicago. Photometric stereo uses multiple ...Show More

Surface shape studies of the art of Paul Gauguin

Oliver Cossairt;Xiang Huang;Nathan Matsuda;Harriet Stratis;Mary Broadway;Jack Tumblin;Greg Bearman;Eric Doehne;Aggelos Katsaggelos;Marc Walton

Year: 2015 | Volume: 2 | Conference Paper |

Crowd-sourced mobile phone images for heritage conservation monitoring

Wensen Ma;Marc Walton;Oliver Cossairt;Greg Bearman;Eric Doehne

2015 Digital Heritage
Year: 2015 | Conference Paper |
Cited by: Papers (2)
We propose quantifying color in crowd-sourced images from mobile phones to monitor built heritage over time. Time-lapse color movies in CIE color space can provide information on a large range of deterioration mechanisms, including soiling, biofilm growth, weathering and vandalism. Citizen science can create large-scale geographical coverage of sites difficult to obtain any other way. We show that...Show More

Crowd-sourced mobile phone images for heritage conservation monitoring

Wensen Ma;Marc Walton;Oliver Cossairt;Greg Bearman;Eric Doehne

Year: 2015 | Volume: 1 | Conference Paper |

Near light correction for image relighting and 3D shape recovery

Xiang Huang;Marc Walton;Greg Bearman;Oliver Cossairt

2015 Digital Heritage
Year: 2015 | Conference Paper |
Cited by: Papers (11)
In this paper, we propose a near-light illumination model for image relighting and 3D shape recovery. Classic methods such as used by the popular RTI software from Cultural Heritage Imaging assume that lighting is infinitely far away from the scene. However, this constraint is impossible to achieve in practice: light sources cannot be too far away from the scene due to space and power constraints....Show More

Near light correction for image relighting and 3D shape recovery

Xiang Huang;Marc Walton;Greg Bearman;Oliver Cossairt

Year: 2015 | Volume: 1 | Conference Paper |

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