Distant Viewing Lab

Distant Viewing: Analyzing Large Visual Corpora
Visual Style in Two Network-Era Sitcoms

Distant Viewing Toolkit (DVT)

Deep Learning for Analyzing Large Image Corpora
HILT2019: Image Analysis with Deep Learning

With support from:


In 2010, Taylor Arnold and Lauren Tilton initiated the digital project Photogrammar , which applied image, mapping, and textual analysis to the study of the FSA-OWI photography archive. The subsequently won grants from the NEH and ACLS to build out the project with additional materials and functionality. They have since wrote the book Humanities Data in R (Springer 2015) and several research articles addressing the power of working at the intersection of statistics and the humanities.

Their work on Photogrammar and Humanities Data in R revealed that there were very few methods and tools available for working with images, particularly moving images. This need, combined with an explosion in the predictive power of computer vision over the last several years and an increased set of digitized visual corpora, produced an opportunity to take visual culture in DH seriously. The Distant Viewing Lab was started as a response in 2017. Working prototype of the lab's software and applications can be found through the links on the left.