Abstract:
A number of current face recognition algorithms use face representations found by unsupervised statistical methods. Typically these methods find a set of basis images and...Show MoreMetadata
Abstract:
A number of current face recognition algorithms use face representations found by unsupervised statistical methods. Typically these methods find a set of basis images and represent faces as a linear combination of those images. Principal component analysis (PCA) is a popular example of such methods. The basis images found by PCA depend only on pairwise relationships between pixels in the image database. In a task such as face recognition, in which important information may be contained in the high-order relationships among pixels, it seems reasonable to expect that better basis images may be found by methods sensitive to these high-order statistics. Independent component analysis (ICA), a generalization of PCA, is one such method. We used a version of ICA derived from the principle of optimal information transfer through sigmoidal neurons. ICA was performed on face images in the FERET database under two different architectures, one which treated the images as random variables and the pixels as outcomes, and a second which treated the pixels as random variables and the images as outcomes. The first architecture found spatially local basis images for the faces. The second architecture produced a factorial face code. Both ICA representations were superior to representations based on PCA for recognizing faces across days and changes in expression. A classifier that combined the two ICA representations gave the best performance.
Published in: IEEE Transactions on Neural Networks ( Volume: 13, Issue: 6, November 2002)
University of California, San Diego, La Jolla, CA, USA
Marian Stewart Bartlett (M'99) received the B.S. degree in mathematics and computer science from Middlebury College, Middlebury, VT, in 1988 and the Ph.D. degree in cognitive science and psychology from the University of California-San Diego, La Jolla, in 1998. Her dissertation work was conducted with T. Sejnowski at the Salk Institute.
She is an Assistant Research Professor at the Institute for Neural Computation, Univers...Show More
Marian Stewart Bartlett (M'99) received the B.S. degree in mathematics and computer science from Middlebury College, Middlebury, VT, in 1988 and the Ph.D. degree in cognitive science and psychology from the University of California-San Diego, La Jolla, in 1998. Her dissertation work was conducted with T. Sejnowski at the Salk Institute.
She is an Assistant Research Professor at the Institute for Neural Computation, Univers...View more
University of California, San Diego, La Jolla, CA, USA
Javier R. Movellan (M'99) was born in Palencia, Spain, and received the B.S. degree from the Universidad Autonoma de Madrid, Madrid, Spain. He was a Fulbright Scholar at the University of California-Berkeley, Berkeley, and received the Ph.D. degree from the same university in 1989.
He was a Research Associate with Carnegie-Mellon University, Pittsburgh, PA, from 1989 to 1993, and an Assistant Professor with the Department ...Show More
Javier R. Movellan (M'99) was born in Palencia, Spain, and received the B.S. degree from the Universidad Autonoma de Madrid, Madrid, Spain. He was a Fulbright Scholar at the University of California-Berkeley, Berkeley, and received the Ph.D. degree from the same university in 1989.
He was a Research Associate with Carnegie-Mellon University, Pittsburgh, PA, from 1989 to 1993, and an Assistant Professor with the Department ...View more
University of California, San Diego, La Jolla, CA, USA
Howard Hughes Medical Institute, CA, USA
Terrence J. Sejnowski (S'83–SM'91–F'00) received the B.S. degree in physics from the Case Western Reserve University, Cleveland, OH, and the Ph.D. degree in physics from Princeton University, Princeton, NJ, in 1978.
In 1982, he joined the faculty of the Department of Biophysics at Johns Hopkins University, Baltimore, MD. He is an Investigator with the Howard Hughes Medical Institute and a Professor at The Salk Institute fo...Show More
Terrence J. Sejnowski (S'83–SM'91–F'00) received the B.S. degree in physics from the Case Western Reserve University, Cleveland, OH, and the Ph.D. degree in physics from Princeton University, Princeton, NJ, in 1978.
In 1982, he joined the faculty of the Department of Biophysics at Johns Hopkins University, Baltimore, MD. He is an Investigator with the Howard Hughes Medical Institute and a Professor at The Salk Institute fo...View more
Contents University of California, San Diego, La Jolla, CA, USA
Marian Stewart Bartlett (M'99) received the B.S. degree in mathematics and computer science from Middlebury College, Middlebury, VT, in 1988 and the Ph.D. degree in cognitive science and psychology from the University of California-San Diego, La Jolla, in 1998. Her dissertation work was conducted with T. Sejnowski at the Salk Institute.
She is an Assistant Research Professor at the Institute for Neural Computation, University of California-San Diego. Her interests include approaches to image analysis through unsupervised learning, with a focus on face recognition and expression analysis. She is presently exploring probabilistic dynamical models and their application to facial expression analysis at the University of California-San Diego. She has also studied perceptual and cognitive processes with V.S. Ramachandran at the University of California-San Diego, the Cognitive Neuroscience Section of the National Institutes of Health, the Department of Brain and Cognitive Sciences at Massachusetts Institute of Technology, Cambridge, and the Brain and Perception Laboratory at the University of Bristol, U.K.
Marian Stewart Bartlett (M'99) received the B.S. degree in mathematics and computer science from Middlebury College, Middlebury, VT, in 1988 and the Ph.D. degree in cognitive science and psychology from the University of California-San Diego, La Jolla, in 1998. Her dissertation work was conducted with T. Sejnowski at the Salk Institute.
She is an Assistant Research Professor at the Institute for Neural Computation, University of California-San Diego. Her interests include approaches to image analysis through unsupervised learning, with a focus on face recognition and expression analysis. She is presently exploring probabilistic dynamical models and their application to facial expression analysis at the University of California-San Diego. She has also studied perceptual and cognitive processes with V.S. Ramachandran at the University of California-San Diego, the Cognitive Neuroscience Section of the National Institutes of Health, the Department of Brain and Cognitive Sciences at Massachusetts Institute of Technology, Cambridge, and the Brain and Perception Laboratory at the University of Bristol, U.K.View more
University of California, San Diego, La Jolla, CA, USA
Javier R. Movellan (M'99) was born in Palencia, Spain, and received the B.S. degree from the Universidad Autonoma de Madrid, Madrid, Spain. He was a Fulbright Scholar at the University of California-Berkeley, Berkeley, and received the Ph.D. degree from the same university in 1989.
He was a Research Associate with Carnegie-Mellon University, Pittsburgh, PA, from 1989 to 1993, and an Assistant Professor with the Department of Cognitive Science, University of California-San Diego (USCD), La Jolla, from 1993 to 2001. He currently is a Research Associate with the Institute for Neural Computation and head of the Machine Perception Laboratory at UCSD. His research interests include the development of perceptual computer interfaces (i.e., system that recognize and react to natural speech commands, expressions, gestures, and body motions), analyzing the statistical structure of natural signals in order to help understand how the brain works, and the application of stochastic processes and probability theory to the study of the brain, behavior, and computation.
Javier R. Movellan (M'99) was born in Palencia, Spain, and received the B.S. degree from the Universidad Autonoma de Madrid, Madrid, Spain. He was a Fulbright Scholar at the University of California-Berkeley, Berkeley, and received the Ph.D. degree from the same university in 1989.
He was a Research Associate with Carnegie-Mellon University, Pittsburgh, PA, from 1989 to 1993, and an Assistant Professor with the Department of Cognitive Science, University of California-San Diego (USCD), La Jolla, from 1993 to 2001. He currently is a Research Associate with the Institute for Neural Computation and head of the Machine Perception Laboratory at UCSD. His research interests include the development of perceptual computer interfaces (i.e., system that recognize and react to natural speech commands, expressions, gestures, and body motions), analyzing the statistical structure of natural signals in order to help understand how the brain works, and the application of stochastic processes and probability theory to the study of the brain, behavior, and computation.View more
University of California, San Diego, La Jolla, CA, USA
Howard Hughes Medical Institute, CA, USA
Terrence J. Sejnowski (S'83–SM'91–F'00) received the B.S. degree in physics from the Case Western Reserve University, Cleveland, OH, and the Ph.D. degree in physics from Princeton University, Princeton, NJ, in 1978.
In 1982, he joined the faculty of the Department of Biophysics at Johns Hopkins University, Baltimore, MD. He is an Investigator with the Howard Hughes Medical Institute and a Professor at The Salk Institute for Biological Studies, La Jolla, CA, where he directs the Computational Neurobiology Laboratory, and Professor of Biology at the University of California-San Diego, La Jolla. The long-range goal his research is to build linking principles from brain to behavior using computational models. This goal is being pursued with a combination of theoretical and experimental approaches at several levels of investigation ranging from the biophysical level to the systems level. The issues addressed by this research include how sensory information is represented in the visual cortex.
Dr. Sejnowski received the IEEE Neural Networks Pioneer Award in 2002.
Terrence J. Sejnowski (S'83–SM'91–F'00) received the B.S. degree in physics from the Case Western Reserve University, Cleveland, OH, and the Ph.D. degree in physics from Princeton University, Princeton, NJ, in 1978.
In 1982, he joined the faculty of the Department of Biophysics at Johns Hopkins University, Baltimore, MD. He is an Investigator with the Howard Hughes Medical Institute and a Professor at The Salk Institute for Biological Studies, La Jolla, CA, where he directs the Computational Neurobiology Laboratory, and Professor of Biology at the University of California-San Diego, La Jolla. The long-range goal his research is to build linking principles from brain to behavior using computational models. This goal is being pursued with a combination of theoretical and experimental approaches at several levels of investigation ranging from the biophysical level to the systems level. The issues addressed by this research include how sensory information is represented in the visual cortex.
Dr. Sejnowski received the IEEE Neural Networks Pioneer Award in 2002.View more
