Estimation of User-Specific Visual Attention Considering Individual Tendency toward Gazed Objects
Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama · 2020
An estimation method of user-specific visual attention considering individual tendency toward gazed objects is presented in this paper. For realization the user-specific visual attention for images, it can be effective to use the past gaze tendency of a target user and gaze data obtained from other users. However, the collaborative use of these information is difficult since there may be no gaze data obtained from other users. Then the proposed method focuses on the saliency map and enables the collaborative use of those information for estimation of user-specific visual attention. It is confirmed that the estimation accuracy of the proposed method improved by approximately 20% compared to the state-of-the-art saliency estimation method by performing the experiment.