The Top-down Visual Attention Method with Known Interference Target
Hui Wang, Lijiao Tian, Hong Chang Ke · DEStech Transactions on Computer Science and Engineering · 2017
The simulation of visual attention can improve the efficiency of relevant intelligent applications by finding out most salient locations quickly in images or videos while ignoring redundant information. The paper can reason key features of target based on task scenario, filter the bottom-up visual attention feature channel by top-down method, and propose the top-down visual attention method with known interference target. The proposed method can minimize the time of generating visual saliency map by ensuring the hit rate of mission targets, and improve the efficiency of the search targets based on visual attention.