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Eye Tracking Metrics: A Toolbox for Assessing the Effects of Clutter on Attention Allocation

机译:眼动指标:评估杂物对注意力分配的影响的工具箱

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摘要

Display clutter is a problem that affects operators in various data-rich environments. Clutter measurementtechniques such as image processing and performance measures can provide an estimate of clutter but arelargely not suited to tracing the effects of clutter on the dynamic allocation of attention. Eye tracking is apromising process-oriented tool that can help assess in real-time the attentional costs associated with thedifferent aspects of clutter. In this experiment, we investigated which of a number of eye tracking metricsin the literature are sensitive to clutter. Twenty-two participants were asked to look for a target in static anddynamic images that were classified as either high or low in clutter. Response time and error rate wererecorded, and an eye tracker was used to compute the identified eye tracking metrics. Results showed that,in both the static and dynamic conditions, a large number of eye tracking metrics were significantlyaffected by an increase in clutter. This suggests that eye tracking can be used to supplement other cluttermeasurement techniques by providing information about dynamic attention allocation.
机译:显示混乱是一个影响各种数据丰富环境中的操作员的问题。杂波测量 诸如图像处理和性能指标之类的技术可以估计杂波,但是 在很大程度上不适合追踪混乱对注意力的动态分配的影响。眼动追踪是 有前途的面向过程的工具,可以帮助您实时评估与 不同方面的混乱。在此实验中,我们调查了多种眼动指标中的哪一项 在文学中对杂物很敏感。 22名参与者被要求寻找静态目标和 分类为高或低杂波的动态图像。响应时间和错误率分别为 记录,然后使用眼动仪计算识别出的眼动指标。结果表明, 在静态和动态条件下,大量的眼动指标 受杂物增加的影响。这表明眼动追踪可用于补充其他杂波 提供有关动态注意力分配的信息的测量技术。

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