Seeing the Past with Computers: Experiments with Augmented Reality and Computer Vision for History

Abstract

We focus on two related forms of seeing technology that are changing how some humanists work, but remain untapped and confusing for most scholars and students: computer vision and augmented reality. Computer vision (CV) is a technology that can access, process, analyze, and understand visual information. Consider, for instance, optical character recognition (OCR), which allows computers to read text from digitized print sources. Whereas scholars used to read a few books deeply ("close reading"), OCR has facilitated what Franco Moretti called "distant reading," helping us mine and analyze thousands of books across eras, genres, and subjects. Such quantitative approaches to textual analysis have their critics, but they also hold many lessons for those interested in history. Yet history involves more than just the textual evidence historians have traditionally privileged; traces of the past are also embedded in the visual--photographs, paintings, sketches--and material culture. The proliferation of digitized visual sources presents historians with exciting new technical and theoretical problems and opportunities. The scholars in this collection offer ways of thinking about where we might look for source material, and how we might use CV to analyze those sources, in the context of our research or teaching, to ensure broader, deeper, and more representative understandings of the past. Seeing the Past is in many ways a sequel to PastPlay: Teaching and Learning with Technology (2014), and we return to some of the ideas explored in that volume. Above all, however, this book is a testament to the power of playful experimentation with technology and techniques in our discipline, and in other domains of inquiry, simply to see what happens