A Model of Saliency-Based Visual Attention for Rapid Scene Analysis

@article{Itti2009AMO,
  title={A Model of Saliency-Based Visual Attention for Rapid Scene Analysis},
  author={Laurent Itti and Christof Koch and Ernst Niebur},
  journal={IEEE Trans. Pattern Anal. Mach. Intell.},
  year={2009},
  volume={20},
  pages={1254-1259}
}
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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