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Similarity measures of object selection in interactive applications based on smooth pursuit eye movements

机译:基于平滑追踪眼动的交互式应用中对象选择的相似性度量

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Gaze-based interaction in various digital technologies is a rapidly growing research area. Eye tracking provides an alternative input modality to control interactive contents in computers. Nowadays, eye tracking is not only expected to be a personal assistive technology, but also to be a controller for interactive contents in a public display. Instead of fixational eye movement, smooth pursuit eye movement has been used for object selection in gaze-based interactive applications. However, previous works did not consider various similarity measures for spontaneous object selection. Hence, no information on how different similarity measures affect performance of object selection. To fill this gap, we compared two similarity measures-Euclidean distance and Pearson's product moment coefficient-for object selection. We presented simple interactive applications containing four dynamic objects, each of which was presented subsequently or simultaneously. The participants were asked to select the objects by gazing and following the trajectory of the moving objects. Our results show that object selection with Euclidean distance achieved superior accuracy (78.65%) compared with object selection with Pearson's product moment coefficient (57.38%). In future, our results maybe used as a guideline for development of spontaneous gaze-based interactive application.
机译:各种数字技术中基于注视的交互是一个快速发展的研究领域。眼动追踪提供了另一种输入方式来控制计算机中的交互式内容。如今,眼动追踪不仅有望成为一种个人辅助技术,而且还将成为公共显示器中交互式内容的控制器。在基于注视的交互式应用程序中,平滑注视眼动已被用于对象选择,而不是注视眼动。但是,以前的工作没有考虑自发对象选择的各种相似性度量。因此,没有有关不同相似性度量如何影响对象选择性能的信息。为了填补这一空白,我们比较了两个相似性指标-欧氏距离和皮尔逊积矩系数-用于对象选择。我们介绍了包含四个动态对象的简单交互式应用程序,每个对象随后或同时显示。要求参与者凝视并跟随移动物体的轨迹选择物体。我们的结果表明,与使用Pearson乘积矩系数(57.38%)进行的对象选择相比,使用欧氏距离进行的对象选择具有更高的精度(78.65%)。将来,我们的结果可能会用作开发基于自发注视的交互式应用程序的指南。

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