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Special GRASP Seminar – Fernando De la Torre, Carnegie Mellon University, “Learning Components for Human Sensing”

March 25, 2010 @ 12:00 pm - 1:00 pm

Abstract: Providing
computers with the
ability to understand human behavior from sensory data (e.g. video,
audio, or
wearable sensors) is an essential part of many applications that can
benefit
society such as clinical diagnosis, human computer interaction, and
social
robotics. A critical element in the design of any behavioral sensing
system is
to find a good representation of the data for encoding, segmenting,
classifying
and predicting subtle human behavior. In this talk I will propose
several
extensions of Component Analysis (CA) techniques (e.g. kernel principal
component analysis, support vector machines, and spectral clustering)
that are
able to learn spatio-temporal representations or components useful in
many
human sensing tasks.

In
the first part of the talk I
will give an overview of several ongoing projects in the CMU Human
Sensing
Laboratory, including our current work on depression assessment from
video, as
well as hot-flash detection from wearable sensors. In the second part of
the
talk I will show how several extensions of the CA methods outperform
state-of-the-art algorithms in problems such as temporal alignment of
human
behavior, temporal segmentation/clustering of human activities, joint
segmentation and classification of human behavior, and facial feature
detection
in images. The talk will be adaptive, and I will discuss the topics of
major
interest to the audience.

Presenter

- Learn More

Fernando
De la Torre received his B.Sc. degree in Telecommunications (1994),
M.Sc.
(1996), and Ph. D. (2002) degrees in Electronic Engineering from La
Salle
School of Engineering in Ramon Llull University, Barcelona, Spain. In
1997 and
2000 he was an Assistant and Associate Professor in the Department of
Communications and Signal Theory in Enginyeria La Salle. Since 2005 he
has been
a Research Assistant Professor in the Robotics Institute at Carnegie
Mellon
University. Dr. De la Torre’s research interests include computer vision
and
machine learning, in particular face analysis, optimization and
component
analysis methods, and its applications to human sensing. Dr. De la Torre
co-organized the first workshop on component analysis methods for
modeling,
classification and clustering problems in computer vision in conjunction
with CVPR’07,
and the workshop on human sensing from video jointly with CVPR’06. He
has also
given several tutorials at international conferences (ECCV’06, CVPR’06,
ICME’07, ICPR’08) on the use and extensions of component analysis
methods.
Currently he leads the Component Analysis Laboratory (http://ca.cs.cmu.edu)
and the Human Sensing
Laboratory (http://humansensing.cs.cmu.edu).

Details

Date:
March 25, 2010
Time:
12:00 pm - 1:00 pm
Event Category: