Fernando De la Torre
Wednesday, October 27, 2010
Building 3 Auditorium - 11:00 AM
(Coffee and cookies at 10:30 AM)
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. In particular, the face is one of the most powerful channels of nonverbal communication. Facial expression provides cues about emotional response, regulates interpersonal behavior, and communicates aspects of psychopathology. While people have believed for centuries that facial expressions can reveal what people are thinking and feeling, it is relatively recently that the face has been studied scientifically for what it can tell us about internal states, social behavior, and psychopathology.
In the first part of the talk I will give an overview of several ongoing projects in the CMU Human Sensing Laboratory to infer human behavior from a variety of sensors (video, audio, accelerometers, wearable sensors). In the second part of the talk I will show how several extensions of the Component Analysis techniques (e.g. kernel principal component analysis, support vector machines, spectral clustering) methods outperform state-of-the-art algorithms in problems such as facial feature detection and tracking, facial expression recognition and temporal clustering of facial behavior.
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 and the Human Sensing Laboratory