Distinguished Lecture Series
Speaker: Alexei Efros, Carnegie
Mellon University
Title: Mining Big Visual Data
Time: 2:00pm-3:00pm
Location: Jajodia Auditorium,
Nguyen Engineering
There are an estimated 3.5 trillion
photographs in the world, of which 10% have been taken in the
past 12 months. Facebook alone reports 6 billion photo uploads
per month. Every minute, 72 hours of video are uploaded to
YouTube. Cisco estimates that in the next few years, visual data
(photos and video) will account for over 85% of total internet
traffic. Yet, we currently lack effective computational methods
for making sense of all this mass of visual data. Unlike easily
indexed content, such as text, visual content is not routinely
searched or mined; it's not even hyperlinked. Visual data is
Internet's "digital dark matter" [Perona,2010] -- it's just
sitting there!
Alexei (Alyosha) Efros is an associate
professor at the Robotics Institute and the Computer Science
Department at Carnegie Mellon University. His research is in the
area of computer vision and computer graphics, especially at the
intersection of the two. He is particularly interested in using
data-driven techniques to tackle problems which are very hard to
model parametrically but where large quantities of data are
readily available. Alyosha received his PhD in 2003 from UC
Berkeley under Jitendra Malik and spent the following year as a
post-doctoral fellow in Andrew Zisserman's group in Oxford,
England. Alyosha is a recipient of CVPR Best Paper Award (2006),
NSF CAREER award (2006), Sloan Fellowship (2008), Guggenheim
Fellowship (2008), Okawa Grant (2008), Finmeccanica Career
Development Chair (2010), SIGGRAPH Significant New Researcher
Award (2010), and ECCV Best Paper Honorable Mention (2010).