Title: "Top-down and Bottom-up
Models of Selective Visual Attention"
Division of Biology & Division of Engineering and
Applied Science
California
Abstract:
Although brains possess a paradigmatically massively
parallel architecture, sensory systems employs a serial computational strategy
to select ``interesting" objects in any scene for further processing,
including access to short-term memory, planning and awareness. In the visual
system of human and monkeys, selective visual attention is guided by a rapid,
task-independent, stimulus-driven saliency-based form of selection process as
well as by a slower, volitional controlled top-down selection process. I will
describe two detailed computational accounts of both selection mechanisms and
discuss their implications for the underlying neuronal processes in the
primate's visual system.
For more information, see http://www.klab.caltech.edu