From gaze plots to eye fixation patterns using a clustering method based on Hausdorff distances

G. Drusch, J. Bastien, J. Dinet
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引用次数: 12

Abstract

Eye-tracking studies have provided us with interesting findings regarding the way users explore Web pages. Usually, visual fixations are represented using gaze plots and heatmaps. Probably one of the most cited studies on Web page exploration is the one by Nielsen [15] who demonstrated that users often read Web pages in an F-shaped pattern. However, this conclusion is based on aggregated data that do not represent any real user. In order to characterize and to compare scanpaths so as to uncover possible scan-patterns, a clustering method based on the Hausdorff distance has been applied to the data from 113 users. The results have shown that scan-patterns could be identified. Groups of users have been identified and their behaviors have been described with diverse eye-tracking metrics. The contributions of this study are outlined as well as its drawbacks. Research perspectives are proposed.
利用基于Hausdorff距离的聚类方法从注视图到注视模式
眼球追踪研究为我们提供了关于用户浏览网页方式的有趣发现。通常,视觉注视用注视图和热图来表示。关于网页探索,被引用最多的研究之一可能是Nielsen[15]的研究,该研究表明,用户通常以f形模式阅读网页。然而,这个结论是基于聚合的数据,并不代表任何真实的用户。为了对扫描路径进行表征和比较,从而揭示可能的扫描模式,对113个用户的数据采用了基于Hausdorff距离的聚类方法。结果表明,扫描模式是可以识别的。用户群体已经被识别出来,他们的行为已经用不同的眼球追踪指标来描述。本文概述了本研究的贡献和不足。提出了研究展望。
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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