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Products for Grant HD-248360-16

Scientific Workflows, Image Analysis, and Visual Stylometry in the Digital Analysis of Art
Catherine Buell, Fitchburg State University

Grant details:

WAIVS website (Web Resources)
Title: WAIVS website
Author: Catherine Buell
Author: Ricky Sethi
Author: William Seeley
Abstract: The WAIVS website serves as an introduction to the future WAIVS interface, a timeline of events, and eventually a portal for usage.
Year: 2016
Primary URL:
Primary URL Description: Homepage for WAIVS

Making WAIVS! (Computer Program)
Title: Making WAIVS!
Author: Catherine Buell
Author: Ricky Sethi
Author: Allen Perry
Author: William Ianacci
Author: Peter Cole
Abstract: Welcome to the WAIVS The goal of our project is to develop a tool called WAIVS (Workflows for Analysis of Images and Visual Stylometry) for digital image analysis of paintings that is powerful enough to support advanced research in computer science, cognitive science, art history, and the philosophy of art while providing an accessible interface that can be used by researchers or students with little or no computer science background. A scientific workflow made in WAIVS is essentially a computer program. So once the user designs the workflow, they can simply click a button to conduct the analysis. Scientific workflows are different from ordinary flowcharts in that they can be directly executed. Once the user designs the workflow, they can simply click the run button to execute the program and conduct the analysis. WAIVS, built upon the Wings workflow system, includes the latest computer vision and artistic style algorithms.
Year: 2017
Primary URL:
Primary URL Description: This URL brings the user to the tutorials and log-in screen.
Access Model: Subsciption only (right now)
Programming Language/Platform: WINGS supported.
Source Available?: No

Reproducibility in computer vision: Towards open publication of image analysis experiments as semantic workflows (Conference Paper/Presentation)
Title: Reproducibility in computer vision: Towards open publication of image analysis experiments as semantic workflows
Author: Ricky J. Sethi
Author: Yolanda Gil
Abstract: Reproducibility of research is an area of growing concern in computer vision. Scientific workflows provide a structured methodology for standardized replication and testing of state-of-the-art models, open publication of datasets and software together, and ease of analysis by re-using pre-existing components. In this paper, we present initial work in developing a framework that will allow reuse and extension of many computer vision methods, as well as allowing easy reproducibility of analytical results, by publishing dadasets and workflows packaged together as linked data. Our approach uses the WINGS semantic workflow system which validates semantic constraints of the computer vision algorithms, making it easy for non-experts to correctly apply state-of-the-art image processing methods to their data. We show the ease of use of semantic workflows for reproducibility in computer vision by both utilizing pre-developed workflow fragments and developing novel computer vision workflow fragments for a video activity recognition task, analysis of multimedia web content, and the analysis of artistic style in paintings using convolutional neural networks.
Date: 2016-10-30
Primary URL:
Primary URL Description: IEEE DOI
Conference Name: 2016 IEEE 12th International Conference on e-Science (e-Science)

What Can Cognitive Science Tell Us about Art? (Conference Paper/Presentation)
Title: What Can Cognitive Science Tell Us about Art?
Author: William P. Seeley
Abstract: There has been an explosion of interest in the marriage of cognitive science and aesthetics in recent years. However, some prominent philosophers (Alva Noë, Strange Tools, Hill and Wang, 2016) and art critics (Blake Gopnik, “Aesthetic Science and Artistic Knowledge,” in eds. Arthur Shimamura & Stephen Palmer, Aesthetic Science: Connecting Minds, Brains, and Experience, Oxford, 2013) have questioned whether this research truly adds anything to our understanding of art. The question is whether cognitive science and aesthetics is looking for art in the right place. Can an investigation of our ordinary psychological engagement with artworks reveal what makes this category of artifacts unique and so deeply meaningful to us? Bill Seeley will discuss how recent research in visual stylometry and machine learning has been used to help answer this skeptical concern.
Date: 03/06/2017
Conference Name: Franklin W. Olin College of Engineering, Needham, Massachusetts.

A Question of Artistic Style: Digital Image Analysis and the Classification of Paintings (Conference Paper/Presentation)
Title: A Question of Artistic Style: Digital Image Analysis and the Classification of Paintings
Author: William P. Seeley and Catherine A. Buell
Abstract: Recent interdisciplinary research in visual stylometry employs digital image analysis algorithms to study the image features and statistics that underwrite our experience and understanding of artworks. This research brings philosophers, psychologists, computer scientists, and art historians together to explore the formal image qualities that define artistic style. We introduce the field of visual stylometry, discuss it's implications for our understanding of both the nature of categories of art and the role artistic style plays in our engagement with artworks. We then discuss the results of our research employing entropy analyses and discrete tonal analyses to classify paintings by school (Impressionism/Hudson River School) and medium/technique (Wyeth/egg-tempura/watercolor).
Date: 04/07/2017
Conference Name: Pacific Division Meeting of the American Society for Aesthetics, Asilomar Conference Grounds, Pacific Grove, California.