A Visual Attention Computational Model Based on Edge Detection
Yuwei Zhang, Ke Deng, Yongcai Pan, Qingzheng Liu · 2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) · 2019
In view of the inadequacy of Itti's computational model of visual attention mechanism in significance region detection, an improved computational model of visual attention based on edge detection was proposed here. It is based on the human eye's perception advantage of the edge shape information of the target object. On the basis of Itti model, this model can improve the extraction effect of significant regions in visual attention computing model by introducing edge information, and can segment significant regions more accurately. The experiment shows that the success rate of target object contour detection in this method can reach 91%, which is higher than the traditional detection method in calculation speed, and the target object contour recognition effect is better.