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A model of saliency-based visual attention for rapid scene analysis
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.
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Olshausen, B., Anderson, C., & Van Essen, D. (1993) · The Journal of Neuroscience · doi:10.1523/jneurosci.13-11-04700.1993 · Cited by 908
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Metadata
- Authors
- Itti, L., Koch, C., & Niebur, E.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1998
- Volume
- 20
- Issue
- 11
- Pages
- 1254-1259
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2128272608
- Cited by
- 11,271
- References
- 1
- FWCI
- 33.56
- Type
- journal article
- Language
- en
- Open access
- closed
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