A model of saliency-based visual attention for rapid scene analysis

A model of saliency-based visual attention for rapid scene analysis

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 salie...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence 1998-11, Vol.20 (11), p.1254-1259
Hauptverfasser: Itti, L., Koch, C., Niebur, E.
Format: Artikel
Sprache:eng
Schlagworte:
Biological system modeling
Brain modeling
Computer architecture
Feature extraction
Hardware
Image analysis
Layout
Neural networks
Object detection
Visual system
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Beschreibung
Zusammenfassung: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.
ISSN:0162-8828
1939-3539
DOI:10.1109/34.730558