Visual attention analysis and prediction on human faces with mole
Nowadays visual attention has been applied to many research and application problems. Different algorithms from low level to high level have been developed to detect the saliency map. For images with human face, high-level factors like mole may influence the visual attention. To investigate visual attention on human face with mole, we construct a Visual Attention database for Faces with Mole (VAFM) that contains face images, fixation density maps (FDM), landmark points as well as eye tracking data. Then we build visual attention model for face images with mole combining low-level saliency algorithms and high-level feature. Compared with the traditional low-level saliency algorithms, the proposed model perform better on our dataset.