Target Features Affect Visual Search, A Study of Eye Fixations
This work provides incremental insights into human visual search behavior, which could inform the design of better computer vision systems or user interfaces.
The study analyzed the COCO-Search18 dataset to examine how target size and eccentricity influence human visual search performance, finding that larger and more eccentric targets are detected faster with fewer eye fixations.
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.