首页> 外文会议>2016 IEEE Second Workshop on Eye Tracking and Visualization >In the pursuit of (ground) truth: a hand-labelling tool for eye movements recorded during dynamic scene viewing
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In the pursuit of (ground) truth: a hand-labelling tool for eye movements recorded during dynamic scene viewing

机译:追求(地面)真相:一种用于在动态场景观看过程中记录眼动的手动标记工具

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We here present parts of our ongoing work to facilitate the largescale analysis of smooth pursuit eye movements made while viewing dynamic natural scenes. Classification of smooth pursuit episodes can be difficult in the presence of eye-tracking noise, and we thus recently proposed an algorithm that clusters gaze recordings from several observers in order to improve classification robustness. We now implemented a publicly available tool that allows for generation of a ground truth benchmark by assisted hand-labelling of video gaze data. Based on the labelling produced with the tool we present preliminary evaluation results for our smooth pursuit classification approach in comparison to state-of-the-art algorithms. Overall, human observers spend more than 12% of their viewing time performing smooth pursuit, which emphasizes the importance of investigating smooth pursuit behaviour in naturalistic contexts.
机译:在这里,我们介绍了正在进行的工作的一部分,以促进在查看动态自然场景时进行的平滑跟踪眼睛运动的大规模分析。在存在眼动追踪噪声的情况下,对平滑追随发作的分类可能很困难,因此我们最近提出了一种对来自多个观察者的凝视记录进行聚类的算法,以提高分类的鲁棒性。现在,我们实施了一个公开可用的工具,该工具可通过辅助对视频注视数据进行手动标记来生成基本事实基准。根据使用该工具产生的标签,我们提供了与最新算法相比,我们的平滑追击分类方法的初步评估结果。总体而言,人类观察者花费了超过12%的观看时间来进行平稳追踪,这强调了在自然主义语境中研究平稳追踪行为的重要性。

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