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A Model of Saliency-based Visual Attention for Rapid Scene Analysis (1998)
| Content Provider | CiteSeerX |
|---|---|
| Author | Niebur, Ernst Koch, Christof Itti, Laurent |
| 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. Index terms: Visual attention, scene analysis, feature extraction, target detection, visual search. \Pi I. Introduction Primates have a remarkable ability to interpret complex scenes in real time, despite the limited speed of the neuronal hardware available for such tasks. Intermediate and higher visual processes appear to select a subset of the available sensory information before further processing [1], most likely to reduce the complexity of scene analysis [2]. This selection appears to be implemented in the ... |
| File Format | |
| Publisher Date | 1998-01-01 |
| Access Restriction | Open |
| Subject Keyword | Attended Location Remarkable Ability Feature Extraction Visual Attention System Visual Search Target Detection Single Topographical Saliency Map Scene Understanding Complex Scene Early Primate Visual System Efficient Manner Saliency-based Visual Attention Available Sensory Information Neuronal Architecture Complex Problem Introduction Primate Neuronal Hardware Limited Speed Visual Attention Dynamical Neural Network Index Term Scene Analysis Conspicuous Location Rapid Scene Analysis Multiscale Image Feature Real Time Visual Process |
| Content Type | Text |
