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J. C. Diop, Upstream: Robotic Vision, Neuroscience-based strategies give robots a new outlook, Technology Review, Vol. 105, No. 8, p. 33, Oct 2002.
Abstract: There are some sights and noises that people just can?t help but notice. Indeed, research in neuroscience now suggests that the recognition of salient objects is a key part of how we make sense of our environment. But building robots that can intelligently pick out items of interest using sight or sound remains a daunting challenge. So a handful of engineers are working on a new approach called selective-attention modeling, which attempts to program robots to evaluate scenes critically as some neuroscientists believe people do. ``General scene understanding is the Holy Grail for computer vision,'' says University of Southern California computer scientist Laurent Itti. Neuroscience-based algorithms, he contends, ``should be the new approach.''
Keywords: Visual perception ; research ; robots
Themes: Computational Modeling, Computer Vision, Beobots
Copyright © 2000-2007 by the University of Southern California, iLab and Prof. Laurent Itti.
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