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Using Computers to Better Understand Art


Detail of "The Morteratsch Glacier, Upper Engadine Valley, Pontresina," by Albert Bierstadt, 1895.

Fitchburge State University professor Ricky J. Sethi discusses the use of computational and statistical methods to uncover unique insights about artists and artworks.

Credit: Wikiart

Visual stylometry is a new research field designed to measure artistic style via computational and statistical methods to uncover unique insights about artists and artworks, writes Fitchburg State University professor Ricky J. Sethi.

"Computer analysis of even previously well-studied images can yield new relationships that aren't necessarily apparent to people, such as Gaugin's printmaking methods," he says. "In fact, these techniques could actually help us discover how humans perceive artworks."

Sethi says his team, composed of experts in computer science, art philosophy, and cognitive science, is developing a digital image-analysis tool for studying paintings called Workflows for Analysis of Images and Visual Stylometry (WAIVS). Based on the Wings workflow system, WAIVS enables users to build analyses in the same manner as drawing a flowchart. For example, to compare tonal analyses of an entire painting and the background alone would not require creating complex computer software, but instead a simple diagram of the process.

"WAIVS includes not just discrete tonal analysis but other image-analysis algorithms, including the latest computer-vision and artistic-style algorithms," Sethi says.

He also notes his group has incorporated into WAIVS convolutional neural network methods for separating artwork style from content.

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