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.

翻译：视觉搜索是指在视觉显示的一组分散物体中寻找目标对象的任务,本文根据对COCO-Search18数据集的独立分析,调查人类参与者在视觉搜索期间的表现如何受到不同参数的影响,例如目标对象的大小和偏心度等参数的影响,我们还研究参与者的误差率与搜索性能之间的关系。我们的研究表明,在固定次数较少的情况下,发现一个更大、更偏心的目标更快。我们的图形代码可在https://github.com/Manooosh-Samiei/COSearch18_Ananaexy上公开查阅。