A Visual Attention Model for Dynamic Scenes Based on Two-Pathway Processing in Brain

Abstract

In this paper, a visual attention model for dynamic scenes based on two-pathway processing in brain is proposed. A saliency map is created to measure the static features, and a motion conspicuity map is created to measure the dynamic feature. Both maps are integrated in an IFNN which is employed to simulate the interactive aspects of two-pathway processing in brain. Selection of attention is accomplished by the interspike interval of the neural network. The experiments results show the effective and efficient performance of the model.