Assessing visual search performance using a novel dynamic naturalistic scene.
Assessing visual search performance using a novel dynamic naturalistic scene.
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DOI：
10.1167/jov.21.1.5
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发表时间：
2021-01-04
影响因子：
1.8
通讯作者：
Merabet LB
中科院分区：
文献类型：
--
作者：
Bennett CR;Bex PJ;Merabet LB
日常活动需要在动态和复杂的场景中不断搜索和跟踪视觉目标。评估视觉搜索性能的经典工作主要是使用简单的几何形状，图案和静态背景。最近，已经有一个转向调查视觉搜索在更自然的动态场景中使用虚拟现实（VR）为基础的范例。在这个方向上，我们开发了一个第一人称视角VR环境，结合眼动跟踪，以捕捉各种客观的措施。参与者被指示在拥挤的走廊环境中寻找预选的人类目标。根据扫视和平滑追踪眼球运动行为对表现进行量化。为了评估任务难度的影响，我们操纵了视觉场景的因素，包括人群密度（即，周围干扰物的数量）和环境杂乱的存在。一般来说，结果显示，随着人群密度的增加，表现越来越差。相比之下，视觉混乱的存在没有影响。这些结果表明，视觉搜索性能可以使用基于VR的自然动态场景和高行为相关性进行调查。该参与平台还可以在评估各种感兴趣的临床人群中的视觉搜索中具有实用性。
Daily activities require the constant searching and tracking of visual targets in dynamic and complex scenes. Classic work assessing visual search performance has been dominated by the use of simple geometric shapes, patterns, and static backgrounds. Recently, there has been a shift toward investigating visual search in more naturalistic dynamic scenes using virtual reality (VR)-based paradigms. In this direction, we have developed a first-person perspective VR environment combined with eye tracking for the capture of a variety of objective measures. Participants were instructed to search for a preselected human target walking in a crowded hallway setting. Performance was quantified based on saccade and smooth pursuit ocular motor behavior. To assess the effect of task difficulty, we manipulated factors of the visual scene, including crowd density (i.e., number of surrounding distractors) and the presence of environmental clutter. In general, results showed a pattern of worsening performance with increasing crowd density. In contrast, the presence of visual clutter had no effect. These results demonstrate how visual search performance can be investigated using VR-based naturalistic dynamic scenes and with high behavioral relevance. This engaging platform may also have utility in assessing visual search in a variety of clinical populations of interest.
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