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SUMMARY:Generative face models for image understanding - Brian Amberg (Uni
 versity of Basel)
DTSTART:20090630T144000Z
DTEND:20090630T150000Z
UID:TALK18591@talks.cam.ac.uk
CONTACT:Dr Fabien Petitcolas
DESCRIPTION:*Abstract*: Humans excel at the task of image understanding. W
 hen we see a face we immediately infer if the person is male or female\, a
 ttractive or not\, young or old\, hostile or friendly or just a boring spe
 aker. For computers this is much harder\, but some progress has been made.
  In this talk I'll argue that for image understanding strong prior knowled
 ge is needed. Humans have acquired this knowledge over the course of their
  phylogenesis and ontogenesis\, while we are still very much trying to for
 ce-feed computers by hand. I'll introduce you to generative face models to
  be used as prior knowledge\, and I'll demonstrate a range of different us
 es of these models which I've encountered during my thesis. I hope to give
  you an overview of the state of the art such that you know the possibilit
 ies and limitations of generative face models for image understanding.\n\n
 *Biography*: In 2005 Brian Amberg achieved a masters degree in Computer Sc
 ience (Dipl. Inf.) at the University of Freiburg (Germany) with a minor in
  Cognitive Science. Since then he works as a PhD student at the University
  of Basel (Switzerland)\, creating a system for expression manipulation in
  video streams and dabbling in many related topics. His research focuses o
 n computer vision\, and so far mainly on face understanding with the help 
 of generative models.
LOCATION:Large public lecture room\, Microsoft Research\, Roger Needham Bu
 ilding\, 7 J J Thomson Avenue\, Cambridge CB3 0FB
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