Takeo Kanade
Robotics Institute Carnegie Mellon University Pittsburgh,
PA 15213 USA
Abstract
Computer
analysis of human face images includes detection of faces, identification of
people, and understanding of expression. Among these three tasks, facial
expression has been the least studied, and most of the past work on facial
expression tried to recognize a small set of emotions, such as joy, disgust,
and surprise. This practice may follow from the work of Darwin, who proposed
that emotions have corresponding prototypic facial expressions. In everyday
life, however, such prototypic expressions occur relatively infrequently;
instead, emotion is communicated more often by subtle changes in one or a few
discrete features. FACS-code Action Units, defined by Ekman, are one such
representation accepted in the psychology community.
In collaboration
with psychologists, we have been developing a system for automatically
recognizing facial action units. This talk will
present the current version
of the system. The system uses a 3D-Active Appearance Model to align a face
image and transform it to a
person-specific canonical coordinate frame.
This transformation can remove appearance changes due to changes of head pose
and relative illumination direction. In this transformed image frame, we
perform detailed analysis of both facial motion and facial appearance changes,
results of which are fed to an action-unit
recognizer.
Bio
Takeo Kanade is the U. A. and Helen Whitaker
University Professor of Computer Science and Robotics at Carnegie Mellon
University. He received his Doctoral degree in Electrical Engineering from
Kyoto University, Japan, in 1974. After holding a faculty position in the
Department of Information Science, Kyoto University, he joined Carnegie Mellon
University in 1980. He was the Director of the Robotics Institute from 1992 to
2001.
Dr. Kanade works in multiple areas of robotics: computer vision,
sensors, multi-media, autonomous ground and air mobile robots, and
medical
robotics. He has written more than 300 technical papers and reports in these
areas, and holds more than 20 patents. He has been the principal investigator
of more than a dozen major vision and robotics projects at Carnegie
Mellon.
Dr. Kanade has been elected to the National Academy of
Engineering (1997) and the American Academy of Arts and Sciences (2004). He is
a Fellow of the IEEE, a Fellow of the ACM, a Founding Fellow of American
Association of Artificial Intelligence (AAAI), and the former and founding
editor of International Journal of Computer Vision. He has received several
awards, including the C&C Award, Joseph Engelberger Award, FIT Funai
Accomplishment Award, Allen Newell Research Excellence Award, JARA Award,
Accomplishment Award of Japanese Society of Artificial Intelligence, and Marr
Prize Award.
Overview and Summary of the Face Recognition Grand Challenge
P. Jonathon Phillips
Program Manager, National Institute of
Standards and Technology Gaithersburg, MD 20899 USA
Abstract
Over the last couple of years, face
recognition researchers have been developing new techniques. These developments
are being fueled
by advances in computer vision techniques, computer design,
sensor design, and interest in fielding face recognition systems.
Such
advances hold the promise of reducing the error rate in face recognition
systems by an order of magnitude over Face Recognition
Vendor Test (FRVT)
2002 results. The Face Recognition Grand Challenge (FRGC) is designed to achieve
this performance goal by
presenting to researchers a six-experiment challenge
problem along with data corpus of 50,000 images. The data consists of 3D scans
and high resolution still imagery taken under controlled and uncontrolled
conditions. Over 20 groups have submitted results on over
60 experiments.
This talk will describe the challenge problem, data corpus, presents baseline
performance, preliminary results on natural statistics of facial imagery, and
summarized the results from the submitted results. (This is joint work
with P. Flynn, T. Scruggs, William Worek, Jin Chang, and Jaesik
Min)
BIO
Dr.
Jonathon Phillips is a leading technologist in the fields of computer vision,
biometrics, face recognition, and human identification. He is at National
Institute of Standards and Technology (NIST), where is he program manager for
the Face Recognition Grand Challenge and test director for the Face Recognition
Vendor Test (FRVT) 2005. From 2000-2004, Dr. Phillips was assigned to the
Defense Advanced Projects Agency (DARPA) as program manager for the Human
Identification at a Distance program. He was test director for the FRVT 2002.
For his work on FRVT 2002 he was awarded the Dept. of Commerce Gold Medal. His
current research interests include computer vision, face recognition,
biometrics, digital video processing, developing methods for evaluating
biometric algorithms, and computational psycho-physics. His work has been
reported in print media of record including the New York Times and the
Economist. Prior to joining NIST, he developed and designed the FERET database
collection and FERET evaluations at the US Army Research Laboratory. He received
his BS in mathematics and MS in electronic and computer engineering from George
Mason University, and his Ph.D. in operations research from Rutgers University.
Dr. Phillips has organized two conferences and workshops on face recognition and
three on empirical evaluation. He has co-edited three books on face recognition
and empirical evaluation. He has been guest editor of special issues or sections
of the IEEE Trans. on Pattern Analysis and Machine Intelligence and Computer
Vision and Image Understanding. Dr. Phillips is an Associate Editor for IEEE
Trans. on Pattern Analysis and Machine Intelligence. He is a member of the IEEE.