Kyle Heath : POMI 2020 Workshop

The widespread availability of digital cameras and ubiquitous Internet access have facilitated the creation of massive image collections. These collections can be highly interconnected through implicit links between image pairs viewing the same or similar objects. We apply computer vision techniques to links images into a graph (like text documents on the web) and demonstrate how these Image Webs can provide new ways of browsing massive photo collections and sharing information about things we photograph.

Kyle Heath is a Ph.D. student in the Department of Electrical Engineering at Stanford University. His work with Prof. Leonidas Guibas has focused on wireless camera sensor networks, a field which lies at the intersection of low-power wireless sensing and computer vision. He has developed lightweight distributed computer vision algorithms for tracking moving objects in cluttered environments on resource-constrained wireless sensor platforms. Recent research has focused on methods for organizing and mining information from large image collections.

Kyle holds an M.S. degree in Electrical Engineering from Stanford and a B.S. degree in Computer Engineering from Rose-Hulman Institute of Technology. As a Rose-Hulman undergraduate, he enjoyed building robots for autonomous aerial robotics competitions.