Published November 1998
| public
Journal Article
A model of saliency-based visual attention for rapid scene analysis
- Creators
-
Itti, Laurent
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Koch, Christof
- Niebur, Ernst
Chicago
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Abstract
A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing saliency. The system breaks down the complex problem of scene understanding by rapidly selecting, in a computationally efficient manner, conspicuous locations to be analyzed in detail.
Additional Information
We thank Werner Ritter and Daimler-Benz for the traffic sign images and Pietro Perona and both reviewers for excellent suggestions. This research was supported by the U.S. National Science Foundation, the Center for Neuromorphic Systems Engineering at Caltech, and the U.S. Office of Naval Research.Additional details
- Eprint ID
- 120640
- Resolver ID
- CaltechAUTHORS:20230330-63403000.1
- NSF
- Center for Neuromorphic Systems Engineering, Caltech
- Office of Naval Research (ONR)
- Created
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2023-03-31Created from EPrint's datestamp field
- Updated
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2023-03-31Created from EPrint's last_modified field
- Caltech groups
- Koch Laboratory (KLAB)