PhD, Brown University
Visual Perception, Quantitative Models
My research interests include human perception, memory, and cognition, with an emphasis on computational approaches to modeling human information processing. I received a B.A. in Psychology (1983) from The Catholic University of America, Washington, DC, and a M.S. (1985) and Ph.D. (1988) in Experimental Psychology from Brown University, Providence, RI. Subsequently, I was a Postdoctoral Fellow at the Université de Bourgogne, Dijon, France, supported by the French Embassy to the United States, and at the Ecole Nationale Superieure des Télécommunications, Paris, France. In 1989, I came to the University of Texas at Dallas, where I established a laboratory for visual perception and image/object recognition experiments. In 1994-1996 I participated in two 6 month sabbaticals at the Max Planck Institute for Biological Cybernetics, Tübingen, Germany supported by the Alexander von Humboldt Foundation. There, I worked on a variety of projects aimed at modeling the perceptual information in three-dimensional laser scans of human heads and relating this information to human memory for faces. I have continued this collaboration and have also continued on work at UTD on human memory for faces, and computational models of visual perception. I am currently working on two projects. The first is aimed at understanding how we recognize people from multiple, dynamic, biometric cues to identity. The second involves computational modeling of data from functional neuroimaging experiments.
My research interests include perception, memory, and cognition, with special interests in recognition memory for faces. Recent work in my lab is aimed at understanding how we recognize people, both from moving and static displays. We are also working on comparing human performance on face recognition tasks to the performance of state-of-the-art face recognition algorithms. Another effort in my lab is focused on functional neuroimaging of high level vision, with emphasis on the use of pattern-based classifiers to analyze neural activation patterns.
O'Toole, A. J. & Natu, V. (2013). Computational perspectives on the other race effect. Visual Cognition.
Natu, V. & O'Toole, A. J. (2013). Neural perspectives on the other-race effect. Visual Cognition.
O'Toole, A.J., An, X., Dunlop, J.P., Natu, V. & Phillips, P.J. (2012). Comparing face recognition algorithms to humans on challenging tasks. ACM Transactions on Applied Perception. 9(4), Article 16.