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Cortical Architectures for Stereo Vision
Description
Abstract: Binocular vision provides both a sense of depth and a means of segmenting the visual scene. The use of binocular vision for segmentation depends upon the rapid automatic processing of local groups of visual features. I shall review the similarities between local pattern detection in binocular and monocular vision, presenting evidence that there are common processes and neural mechanisms involved. Using neurophysiological recordings from the striate cortex (V1) and the extrastriate cortical area (V5/MT), it is possible to map the cortical distances and implied neural connectivity that are required for the efficient use of binocular information.
Speaker Bio
Andrew Parker obtained a doctorate from the University of Cambridge and then transferred to Oxford, initially with a Beit Memorial Fellowship, and then held the Rudolph and Ann Rork Light Research Fellowship at St Catherine’s College. After a year as a Visiting Scientist at the MIT Artificial Intelligence Laboratory, he was appointed to a University Lecturership in Physiology at Oxford, where he was awarded the title of Professor in 1996. He is Fellow and Tutor in Physiology at St John’s College and has been awarded a Leverhulme Senior Research Fellowship (2004-5) and a Wolfson Research Merit Award by the Royal Society. In 2002, he was an Invited Visiting Scholar at the Getty Research Institute for visual art in Los Angeles.
Andrew Parker’s research interests cover a wide range of topics in vision, with a particular emphasis on linking neuronal activity to perceptual judgments. His group has made significant advances in the understanding of the physiology of binocular depth and its relationship with other sources of information about three-dimensional shape. This work has probed the cortical stages of binocular processing with a variety of perceptual tasks and techniques, including single-unit in vivo physiology, visual psychophysics, immersive virtual reality, functional brain imaging, human electrophysiology and computational modelling.