Event Location: NSH 1507
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 speciality 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.

Abstract: Every day billions of images are uploaded to the Internet. Together they provide many high-resolution pictures of the world, from panoramic views of natural landscapes to detailed views of what someone had for dinner. This imagery has the potential to drive discoveries in a wide variety of disciplines, from environmental monitoring to cultural anthropology. Significant research progress has been made in automatically extracting information from such imagery. One of the key remaining challenges is that we often don’t know where an image was captured and usually know very little about other geometric properties of the camera, such as orientation and focal length. In other words, most images are not geocalibrated. This talk provides an overview of my work on using novel cues, including partly cloudy days, rainbows, and human faces, to geocalibrate Internet imagery and video.