CVL Seminar: "Component Analysis for Human Sensing" by Fernando De la Torre - Carnegie Mellon University

Tue Apr 16, 2013 11:00 AM

Computer Vision Laboratory
Center for Automation Research
A.V. Williams Building, Room 2120
University of Maryland

Fernando De la Torre
Robotics Institute
Carnegie-Mellon University

Enabling computers to understand human behavior has the potential to revolutionize many areas that 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, spectral clustering) that are able to learn spatio-temporal representations or components useful in many human sensing tasks. In particular, I will show how several extensions of CA methods outperform state-of-the-art algorithms in problems such as facial feature detection and tracking, temporal clustering of human behavior, early detection of activities, non-rigid feature matching, weakly-supervised visual labeling, and robust classification. The talk will be adaptive, and I will discuss the topics of major interest to the audience.

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 2003 he joined the Robotics Institute at Carnegie Mellon University, and since 2010 he has been a Research Associate Professor. 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. He is Associate Editor at IEEE PAMI and leads the Component Analysis Laboratory and the Human Sensing Laboratory.