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Attributes of Subtle Cues for Facilitating Visual Search in Augmented Reality

机译:增强现实中促进视觉搜索的微妙线索属性

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Goal-oriented visual search is performed when a person intentionally seeks a target in the visual environment. In augmented reality (AR) environments, visual search can be facilitated by augmenting virtual cues in the person's field of view. Traditional use of explicit AR cues can potentially degrade visual search performance due to the creation of distortions in the scene. An alternative to explicit cueing, known as subtle cueing, has been proposed as a clutter-neutral method to enhance visual search in video-see-through AR. However, the effects of subtle cueing are still not well understood, and more research is required to determine the optimal methods of applying subtle cueing in AR. We performed two experiments to investigate the variables of scene clutter, subtle cue opacity, size, and shape on visual search performance. We introduce a novel method of experimentally manipulating the scene clutter variable in a natural scene while controlling for other variables. The findings provide supporting evidence for the subtlety of the cue, and show that the clutter conditions of the scene can be used both as a global classifier, as well as a local performance measure.
机译:当人在视觉环境中有意地寻找目标时,执行面向目标的视觉搜索。在增强现实(AR)环境中,可以通过增加人的视野中的虚拟提示来促进视觉搜索。由于场景中会产生失真,因此传统上使用显式AR提示可能会降低视觉搜索性能。已经提出了一种显式提示的替代方法,称为微妙提示,作为一种杂波中性方法,可以增强视频透明AR中的视觉搜索。但是,对微妙提示的效果仍然知之甚少,需要更多的研究来确定在AR中应用微妙提示的最佳方法。我们进行了两个实验来调查场景杂乱,线索的不透明度,大小和形状对视觉搜索性能的影响。我们介绍了一种在控制其他变量的同时实验性地操纵自然场景中的场景杂波变量的新颖方法。这些发现为线索的微妙提供了支持证据,并表明场景的混乱状况既可以用作全局分类器,也可以用作局部性能指标。

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