好莱坞两小时:观看电影片段时眼球运动的手动注释地面真相数据集。

IF 1.3 4区 心理学 Q3 OPHTHALMOLOGY
Ioannis Agtzidis, Mikhail Startsev, Michael Dorr
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引用次数: 6

摘要

在这篇短文中,我们展示了我们对大规模眼动追踪数据集Hollywood2的一个子集的眼动事件的手工注释。我们的标签包括注视、扫视和平滑追求,以及噪声事件类型(后者代表眨眼、跟踪丢失或物理上不可信的信号)。为了获得更一致的注释,注视样本由新手评分员根据基本算法建议进行标记,随后由专家评分员进行校正。总的来说,我们在来自好莱坞的50个随机选择的测试集片段和6个训练集片段对应的记录中注释了眼动事件,这些记录由16名观察者观看,总计约130分钟的凝视数据。在这些标签中,62.4%的样本归为注视,9.1%归为扫视,值得注意的是,24.2%归为追求(其余标记为噪声)。在对我们新收集的注释数据集上发表的15种眼动分类算法进行评估后,我们发现,最新的算法平均表现非常好,甚至在注视和扫视方面达到了人类水平的标记质量,但在平滑追求分类方面,所有算法都有更大的改进空间。该数据集可在https://gin.g-node.org/ioannis.agtzidis/hollywood2_em上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Two hours in Hollywood: A manually annotated ground truth data set of eye movements during movie clip watching.

Two hours in Hollywood: A manually annotated ground truth data set of eye movements during movie clip watching.

Two hours in Hollywood: A manually annotated ground truth data set of eye movements during movie clip watching.

Two hours in Hollywood: A manually annotated ground truth data set of eye movements during movie clip watching.

In this short article we present our manual annotation of the eye movement events in a subset of the large-scale eye tracking data set Hollywood2. Our labels include fixations, saccades, and smooth pursuits, as well as a noise event type (the latter representing either blinks, loss of tracking, or physically implausible signals). In order to achieve more consistent annotations, the gaze samples were labelled by a novice rater based on rudimentary algorithmic suggestions, and subsequently corrected by an expert rater. Overall, we annotated eye movement events in the recordings corresponding to 50 randomly selected test set clips and 6 training set clips from Hollywood2, which were viewed by 16 observers and amount to a total of approximately 130 minutes of gaze data. In these labels, 62.4% of the samples were attributed to fixations, 9.1% - to saccades, and, notably, 24.2% - to pursuit (the remainder marked as noise). After evaluation of 15 published eye movement classification algorithms on our newly collected annotated data set, we found that the most recent algorithms perform very well on average, and even reach human-level labelling quality for fixations and saccades, but all have a much larger room for improvement when it comes to smooth pursuit classification. The data set is made available at https://gin.g-node.org/ioannis.agtzidis/hollywood2_em.

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来源期刊
CiteScore
2.90
自引率
33.30%
发文量
10
审稿时长
10 weeks
期刊介绍: The Journal of Eye Movement Research is an open-access, peer-reviewed scientific periodical devoted to all aspects of oculomotor functioning including methodology of eye recording, neurophysiological and cognitive models, attention, reading, as well as applications in neurology, ergonomy, media research and other areas,
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