Exploring covert attention for generic boosting of saliency models
Xiaoshuai Sun, Hongxun Yao · 2014
Covert attention is an mental ability to attend to a stimulus without shifting ones gaze towards it. The covert attention mechanism allows small spatial displacement during saccadic eye-movements, which we believed to be responsible for the existence of a large number of imperfectly allocated eye fixations in current saliency benchmark datasets. Inspired by this new finding, we propose to use spatial pooling to integrate cover attention into the current saliency models. We test our pooling-based boosting strategy for 20 state-of-the-art attention models on two well acknowledged fixation datasets (YORK-120 & MIT-1003). The experimental results show that our method can stably improve the performance of over 95% of the tested models in the eye fixation prediction task.