Every day millions (perhaps billions) of geotagged images are uploaded to the Internet. Together they provide many high-resolution pictures of the world, from wide-area views of natural landscapes to detailed views of what someone had for dinner. This imagery has the potential to drive discoveries in a wide range of disciplines. The key challenge is the sheer scale of the resource, which necessitates automated approaches to extracting information from the images. This talk consists of three parts: 1) an overview of research in computer vision to create tools to learn about the world from geotagged Internet imagery, 2) a description of my work in using images from publicly available outdoor webcams, and 3) highlights from my recent work exploring the relationship between human appearance and geographic location.

Bio

Nathan Jacobs earned a PhD in Computer Science at Washington University in St. Louis (2010). Since then, he has been an Assistant Professor of Computer Science at the University of Kentucky. Dr. Jacobs' research area is computer vision; his specialty is developing learning-based algorithms and systems for processing large-scale image collections. His current focus is on developing techniques for mining information about people and the natural world from geotagged imagery, including images from social networks, publicly available outdoor webcams, and satellites.