  Visual Search is referred to the task of finding a target object among a set
of distracting objects in a visual display. In this paper, based on an
independent analysis of the COCO-Search18 dataset, we investigate how the
performance of human participants during visual search is affected by different
parameters such as the size and eccentricity of the target object. We also
study the correlation between the error rate of participants and search
performance. Our studies show that a bigger and more eccentric target is found
faster with fewer number of fixations. Our code for the graphics are publicly
available at https://github.com/ManooshSamiei/COCOSearch18_Analysis.
