Finding the outliers in scanpath data

Michael Burch, Ayush Kumar, K. Mueller, Titus Kervezee, Wouter W. L. Nuijten, Rens Oostenbach, Lucas Peeters, Gijs Smit
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引用次数: 9

Abstract

In this paper, we describe the design of an interactive visualization tool for the comparison of eye movement data with a special focus on the outliers. In order to make the tool usable and accessible to anyone with a data science background, we provide a web-based solution by using the Dash library based on the Python programming language and the Python library Plotly. Interactive visualization is very well supported by Dash, which makes the visualization tool easy to use. We support multiple ways of comparing user scanpaths like bounding boxes and Jaccard indices to identify similarities. Moreover, we support matrix reordering to clearly separate the outliers in the scanpaths. We further support the data analyst by complementary views such as gaze plots and visual attention maps.
查找扫描路径数据中的异常值
在本文中,我们描述了一个交互式可视化工具的设计,用于比较眼动数据,并特别关注异常值。为了使具有数据科学背景的任何人都可以使用和访问该工具,我们通过使用基于Python编程语言的Dash库和Python库Plotly提供了一个基于web的解决方案。Dash非常支持交互式可视化,这使得可视化工具易于使用。我们支持多种方法来比较用户扫描路径,如边界框和Jaccard索引来识别相似性。此外,我们支持矩阵重新排序,以清楚地分离扫描路径中的异常值。我们通过诸如凝视图和视觉注意图等补充视图进一步支持数据分析师。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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