@article{Itti_etal98pami,
  author = {L. Itti and C. Koch and E. Niebur},
  title = {A Model of Saliency-Based Visual Attention for Rapid Scene Analysis},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume = {20},
  number = {11},
  pages = {1254-1259},
  month = {Nov},
  year = {1998},
  keywords = {Visual attention ; target detection ; saliency ; image understanding},
  abstract = {A trainable 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.},
  type = {mod;bu;cv},
  file = {http://iLab.usc.edu/publications/doc/Itti_etal98pami.pdf},
  if = {1998 impact factor: 1.417},
}