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Attention and Change Detection

R. Rensink (Nissan CBR), J.K. O'Regan (Université René Descartes), J.J. Clark

In this project we are investigating the processes by which humans visually detect changes in their environment and how to apply this knowledge to building robot vision systems. Psychophysical experiments done with collaborators at the Nissan Cambridge Basic Research Center have shown that people can only detect changes in their visual field if they have allocated visual attention to the aspect of the scene that is changing. If this attentional allocation is disrupted, by a flash of light or a blanking of the image, then otherwise easily seen changes become very difficult to detect. Changes to items in the visual scene which are not attended to cannot be detected. These experiments lead to a model of the human visual system wherein very little direct information about the environment is stored at any given time. This suggests that real-time robot vision systems may be achieved by likewise retaining only sparse descriptions, and updating these descriptions only when scene changes are detected. We are currently implementing such a system in our lab at CIM.
 


Annual Report

Fri Nov 26 23:00:32 GMT 1999