Modeling People from Billions of Photos

Internet and personal photo collections now add up to over a trillion photos, with people being in most of them. The availability of so many photos presents a unique opportunity to model virtually the whole human population. Modeling humans is key to understanding how people interact with the environment, and to future human machine interfaces. In this talk, I will describe our work on 3D shape and motion estimation of a human face from large photo collections, as well as novel techniques for browsing those collections. This represents an exciting breakthrough towards modeling and visualizing any person just from their available photos. Part of this work is now included in Google’s Picasa.

Ira Kemelmacher-Shlizerman is a Postdoctoral researcher in the Department of Computer Science and Engineering at the University of Washington. She received her Ph.D in computer science and applied mathematics at the Weizmann Institute of Science in 2009. Dr. Kemelmacher-Shlizerman works in computer vision and graphics, with a particular interest in developing computational tools for modeling people from Internet and personal photo collections. Ira's recent research was covered by stories in New Scientist, CBS, Discovery News and others. She was also consulting for Google.