Modeling Bottom-Up and Top-Down Visual Attention in Humans and Monkeys – Laurent Itti (Department of Computer Science and Neuroscience Graduate Program, University of Southern California)

January 27, 2009 all-day

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Visual processing of complex natural environments requires animals to combine, in a highly dynamic and adaptive manner, sensory signals that originate from the environment (bottom-up) with behavioral goals and priorities dictated by the task at hand (top-down). Together, bottom-up and top-down influences combine to serve the many tasks which require that we direct attention to the most ”relevant” entities in our visual environment. While much progress has been made in investigating experimentally how humans and other primates may operate such goal-based attentional selection, very little is understood of the general mathematical principles and neuro-computational architectures that subserve the observed behavior. I will describe recent computational work which attacks the problem of developing models of visual attentional selection that are more flexible and can be strongly modulated by the task at hand. I will back the proposed architectures up by comparing their predictions to behavioral recordings from humans and monkeys. I will show examples of applications of these models to real-world vision challenges, using complex stimuli from television programs or modern immersive video games.
Dr. Laurent Itti received his M.S. in Electrical Engineering with a specialization in Image Processing from the Ecole Nationale Superieure des Telecommunications, Paris, France, in 1994. He received his Ph.D. in Computation and Neural Systems from the California Institute of Technology, Pasadena, California, in 2000. He has since then been an Assistant (2000-2006) and Associate (2006-present) professor of Computer Science and voting faculty member of the cross-disciplinary Neuroscience Graduate Program at the University of Southern California (USC), Los Angeles, California. Dr. Itti has authored over 90 peer-reviewed publications in journals, books, and top-ranked conferences. Dr. Itti teaches Artificial Intelligence, Brain Theory and Neural Networks, Introduction to Robotics, Visual Processing, Neuroscience Core Course, Neural Basis for Visually Guided Behavior, and Computational Architectures in Biological Vision. Dr. Itti’s laboratory comprises 15 students, postdocs and engineers, and is recipient of grants by the National Science Foundation, DARPA, the National Geospatial-Intelligence Agency, the Human Frontier Science Program (HFSP), the Office of Naval Research, the Army Research Office, and the National Institutes of Health. Dr. Itti has been distinguished through a number of awards, including the 2008 Okawa Foundation Research Award, being one of the 16 nationally selected speakers at the 2007 National Academy of Engineering’s Frontiers of Engineering Symposium, and serving on Program Committees for several conferences by IEEE.

Center for Language and Speech Processing