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
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.