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Temporal Sequences Quantify the Contributions of Individual Fixations in Complex Perceptual Matching Tasks

机译：时间序列量化单个固定在复杂的感知匹配任务中的贡献

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摘要

Perceptual tasks such as object matching, mammogram interpretation, mental rotation, and satellite imagery change detection often require the assignment of correspondences to fuse information across views. We apply techniques developed for machine translation to the gaze data recorded from a complex perceptual matching task modeled after fingerprint examinations. The gaze data provide temporal sequences that the machine translation algorithm uses to estimate the subjects' assumptions of corresponding regions. Our results show that experts and novices have similar surface behavior, such as the number of fixations made or the duration of fixations. However, the approach applied to data from experts is able to identify more corresponding areas between two prints. The fixations that are associated with clusters that map with high probability to corresponding locations on the other print are likely to have greater utility in a visual matching task. These techniques address a fundamental problem in eye tracking research with perceptual matching tasks: Given that the eyes always point somewhere, which fixations are the most informative and therefore are likely to be relevant for the comparison task?
机译：诸如对象匹配，乳房X线照片解释，思维旋转和卫星图像变化检测之类的感知任务通常需要分配对应关系以融合视图中的信息。我们将针对机器翻译开发的技术应用于通过指纹检查建模的复杂感知匹配任务记录的凝视数据。凝视数据提供了时间序列，机器翻译算法使用这些时间序列来估计对象对相应区域的假设。我们的结果表明，专家和新手的表面行为都相似，例如固定的次数或固定的持续时间。但是，应用于专家数据的方法能够识别两个印刷品之间的更多对应区域。与以高概率映射到其他印刷品上相应位置的聚类相关联的注视在视觉匹配任务中可能会发挥更大的作用。这些技术通过感知匹配任务解决了眼动追踪研究中的一个基本问题：鉴于眼睛总是指向某处，哪种注视最能提供信息，因此可能与比较任务相关？

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