| ECVision indexed and annotated bibliography of cognitive computer vision publications This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1 The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
J. K. {Cutzu, F., Tsotsos}
ABSTRACT
The selective tuning model is a neurobiologically plausible neural network model of visual attention. One of its key predictions is that to simultaneously solve the problems of convergence of neural input and selection of attended items, the portions of the visual neural network that process an attended stimulus must be surrounded by inhibition. To test this hypothesis, we mapped the attentional field around an attended location in a matching task where the subjects attention was directed to a cued target while the distance of a probe item to the target was varied systematically. The main result was that accuracy increased with inter-target separation. The observed pattern of variation of accuracy with distance provided strong evidence in favor of the critical prediction of the model that attention is actively inhibited in the immediate vicinity of an attended location. Tasks involving shading as well as stereo cues that define shape unambiguously. The results show that although stereo disparity information is incorporated by early-vision 3-D mechanisms, it is not used to overturn the default assumptions of lighting and shape. Stereo information is interpreted within the framework of top-left lighting, and a consistent preference for convexity is seen over concavity. |
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