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

被引：7980

作者：

Itti, L ^{[1
]}

Koch, C

Niebur, E

机构：

[1] CALTECH 139 74, Computat & Neural Syst Program, Pasadena, CA 91125 USA

[2] Johns Hopkins Univ, Krieger Mind Brain Inst, Baltimore, MD 21218 USA

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 1998年 / 20卷 / 11期

基金：

美国国家科学基金会;

关键词：

visual attention; scene analysis; feature extraction; target detection; visual search;

D O I：

10.1109/34.730558

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1254 / 1259

页数：6

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