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首页> 外文期刊>Urban Forestry & Urban Greening >How eye-catching are natural features when walking through a park? Eye-tracking responses to videos of walks
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How eye-catching are natural features when walking through a park? Eye-tracking responses to videos of walks

机译：在公园散步时，如何引人注目是自然特征？ 跟踪散步视频的回应

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Since the 1960s researchers have developed a range of techniques for evaluating landscape preference. In parallel with this trend, eye-tracking technology has become cheaper, more mobile and more accurate, heralding a new era of big data capture and analysis for landscape preference. In this project our objective was to capitalise on the increasing mobility, sophistication and cheapness of eye-tracking technology to examine its utility in analysing landscape preference. In the following we describe how we eye-tracked 35 participants as they viewed walks through two different parks in the urban center of Melbourne, Australia. We show how participants dwelt on trees and bushes more than other objects. When we compared this to the time and space that objects occupy, participants overwhelmingly dwelt on artificial objects such as lamp-posts, distant buildings and benches. Overall we provide an exploration and method for analysing eye-tracking data in parks by normalising the dwell time by the content, providing a robust means of comparing different dynamic stimuli such as videos.
机译：自20世纪60年代的研究人员开始了一系列评估景观偏好的技术。与此趋势同时，眼新的技术已经变得更便宜，更加手机更准确，覆盖了大数据捕获的新时代和景观偏好的分析。在这个项目中，我们的目标是利用越来越多的流动性，复杂性和廉价的眼跟踪技术，以检查其公用事业分析景观偏好。在下文中，我们描述了我们如何通过澳大利亚墨尔本市中心的两个不同公园观看的35名参与者。我们展示了参与者如何比其他物品更乐于树木和灌木丛。当我们将其与物体占据的时间和空间进行比较时，参与者在人造物体上压倒性地倾向于灯柱，遥远的建筑物和长椅。总的来，我们提供了一种探讨和方法，用于通过内容标准化停留时间来分析公园中的眼跟踪数据，提供了一种比较不同动态刺激等视频的强大方法。

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