Automated Filtering of Eye Movements Using Dynamic AOI in Multiple Granularity Levels

Automated Filtering of Eye Movements Using Dynamic AOI in Multiple Granularity Levels
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使用多粒度级别的动态 AOI 自动过滤眼球运动

DOI:
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发表时间:
2021
期刊:
Int. J. Multim. Data Eng. Manag.
影响因子:
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通讯作者:
S. Jayarathna
S. Jayarathna
中科院分区:
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文献类型:
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作者:
Gavindya Jayawardena;S. Jayarathna

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眼睛跟踪实验涉及用于分析眼睛凝视数据的感兴趣区域(AOI)。虽然有描绘AOI的工具来提取眼动数据,但它们可能需要用户在眼睛跟踪刺激上手动绘制AOI的边界或使用标记来定义AOI。本文介绍了两种从AOIS中动态过滤眼动数据的新技术,以从多个粒度级别分析眼睛度量。作者结合了预先训练的对象检测器和对象实例分割模型来离线检测视频流中的动态AOI。本研究提出了目标检测器和目标实例分割模型的实现和评估,以找到要集成到实时眼动分析流水线中的最佳模型。作者过滤落在检测到的动态AOI的多边形边界内的凝视数据,并应用对象检测器在公共数据集中寻找包围盒。结果表明,目标检测器产生的动态AOI捕获了60%的眼动,而目标实例分割模型捕获了30%的眼动。
Eye-tracking experiments involve areas of interest (AOIs) for the analysis of eye gaze data. While there are tools to delineate AOIs to extract eye movement data, they may require users to manually draw boundaries of AOIs on eye tracking stimuli or use markers to define AOIs. This paper introduces two novel techniques to dynamically filter eye movement data from AOIs for the analysis of eye metrics from multiple levels of granularity. The authors incorporate pre-trained object detectors and object instance segmentation models for offline detection of dynamic AOIs in video streams. This research presents the implementation and evaluation of object detectors and object instance segmentation models to find the best model to be integrated in a real-time eye movement analysis pipeline. The authors filter gaze data that falls within the polygonal boundaries of detected dynamic AOIs and apply object detector to find bounding-boxes in a public dataset. The results indicate that the dynamic AOIs generated by object detectors capture 60% of eye movements & object instance segmentation models capture 30% of eye movements.
DOI: 10.1371/journal.pone.0203629
发表时间: 2018
期刊: PloS one
影响因子: 3.7
作者:
Krejtz K;Duchowski AT;Niedzielska A;Biele C;Krejtz I
通讯作者: Krejtz I
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DOI: 10.1145/3204493.3204543
发表时间: 2018
期刊: Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications (ETRA '18
影响因子: --
作者:
Gehrer, Nina A.;Schönenberg, Michael;Duchowski, Andrew T.;Krejtz, Krzysztof
通讯作者: Krejtz, Krzysztof