Age-adapted saliency model with depth bias

Visual attention studies in computer vision research have focused on the development of computational attention systems that can detect salient regions in images for adults. Consequently, age differences in scene viewing behavior has rarely been considered. This study quantitatively analyzed the age-related differences in gaze landings during scene viewing for three age groups: children, adults, and elderly. An interesting observation from our analysis is that whereas child observers focus more on the scene foreground, i.e., locations that are near, elderly observers tend to explore the scene background, i.e., locations farther in the scene. Considering this result a framework is proposed in this paper to quantitatively measure the depth bias tendency across age groups. Further, the age impact on exploratory behavior, central bias tendency, and agreement between explored regions within and across the age groups are quantified via analysis. Experimental results show that children exhibit the lowest exploratory behavior level but the highest central bias tendency among the age groups. Further, agreement scores reveal that adults had least agreement with each other in explored regions. The data analysis results were consequently leveraged to develop a more accurate age-adapted saliency model that outperforms existing saliency models that do not consider age.