Abstract

L. Itti, C. Koch, E. Niebur, A Model of Saliency-Based Visual Attention for Rapid Scene Analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 11, pp. 1254-1259, Nov 1998. [1998 impact factor: 1.417] (Cited by 14313)

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.

Keywords: Visual attention ; target detection ; saliency ; image understanding

Themes: Computational Modeling, Model of Bottom-Up Saliency-Based Visual Attention, Computer Vision