  In this study we provide the analysis of eye movement behavior elicited by
low-level feature distinctiveness with a dataset of synthetically-generated
image patterns. Design of visual stimuli was inspired by the ones used in
previous psychophysical experiments, namely in free-viewing and visual
searching tasks, to provide a total of 15 types of stimuli, divided according
to the task and feature to be analyzed. Our interest is to analyze the
influences of low-level feature contrast between a salient region and the rest
of distractors, providing fixation localization characteristics and reaction
time of landing inside the salient region. Eye-tracking data was collected from
34 participants during the viewing of a 230 images dataset. Results show that
saliency is predominantly and distinctively influenced by: 1. feature type, 2.
feature contrast, 3. temporality of fixations, 4. task difficulty and 5. center
bias. This experimentation proposes a new psychophysical basis for saliency
model evaluation using synthetic images.
