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HAA-271801-20

Penn State (University Park, PA 16802-1503)
Elizabeth C. Mansfield (Project Director: January 2020 to present)
James Z. Wang (Co Project Director: May 2020 to present)
Seeing Constable’s Clouds: An Application of Machine Learning to Art Historical Research

The development of computational methods to analyze formal details in paintings, focusing on cloud studies by John Constable and his emulators, documentary photographs, and fine art photographs.  

“Seeing Constable’s Clouds” proposes to use computer vision and machine learning to better understand the visual cues of 19th-century pictorial realism. Realist landscapes by British artist John Constable (1776-1837) are often split into two phases depending on whether they were made before or after an intense period spent observing and painting clouds in 1821-1822. Contemporaries disagreed about the effect this interlude had on the realism of his work, and art historians continue to debate how his empirical approach influenced his style and technique. The project team will use computer vision to seek formal details that art historians may have overlooked or been unable to discern. We will also use machine learning to discover whether there are formal features that contribute to the verisimilitude of three different types of pictorial realism: Constable’s paintings of clouds, fine art photographs of clouds, and research photographs of clouds made for scientific study.

[Grant products][Media coverage]

Project fields:
Art History and Criticism

Program:
Digital Humanities Advancement Grants

Division:
Digital Humanities

Totals:
$48,487 (approved)
$48,487 (awarded)

Grant period:
9/1/2020 – 8/31/2022