  The existing computational visual attention systems have focused on the
objective to basically simulate and understand the concept of visual attention
system in adults. Consequently, the impact of observer's age in scene viewing
behavior has rarely been considered. This study quantitatively analyzed the
age-related differences in gaze landings during scene viewing for three
different class of images: naturals, man-made, and fractals. Observer's of
different age-group have shown different scene viewing tendencies independent
to the class of the image viewed. Several interesting observations are drawn
from the results. First, gaze landings for man-made dataset showed 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.
Second, the quantitative analysis results showed that children exhibit the
lowest exploratory behavior level but the highest central bias tendency among
the age groups and across the different scene categories. Third,
inter-individual similarity metrics reveal that an adult had significantly
lower gaze consistency with children and elderly compared to other adults for
all the scene categories. Finally, these analysis results were consequently
leveraged to develop a more accurate age-adapted saliency model independent to
the image type. The prediction accuracy suggests that our model fits better to
the collected eye-gaze data of the observers belonging to different age groups
than the existing models do.
