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The Briefest of Glances: The Time Course of Natural Scene Understanding

机译:最短概览:自然场景理解的时间过程

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摘要

What information is available from a brief glance at a novel scene? Although previous efforts to answer this question have focused on scene categorization or object detection, real-world scenes contain a wealth of information whose perceptual availability has yet to be explored. We compared image exposure thresholds in several tasks involving basic-level categorization or global-property classification. All thresholds were remarkably short: Observers achieved 75%-correct performance with presentations ranging from 19 to 67 ms, reaching maximum performance at about 100 ms. Global-property categorization was performed with significantly less presentation time than basic-level categorization, which suggests that there exists a time during early visual processing when a scene may be classified as, for example, a large space or navigable, but not yet as a mountain or lake. Comparing the relative availability of visual information reveals bottlenecks in the accumulation of meaning. Understanding these bottlenecks provides critical insight into the computations underlying rapid visual understanding.
机译:简要浏览一下一个新颖的场景可以获得哪些信息?尽管先前为回答这个问题所做的努力都集中在场景分类或对象检测上,但现实世界中的场景包含大量信息,其感知能力尚待探索。我们在涉及基本级别​​分类或全局属性分类的几个任务中比较了图像曝光阈值。所有阈值都非常短:观察者的演示时间从19到67 ms,达到了75%的正确性能,在大约100 ms时达到了最高性能。与基本级别的分类相比,执行全局属性的分类所需的显示时间要少得多,这表明在早期的视觉处理过程中,存在将场景分类为例如大空间或可通行的场景的时间,但尚不存在。山或湖。比较视觉信息的相对可用性,揭示了意义积累中的瓶颈。了解这些瓶颈可提供对快速视觉理解基础的计算的关键见解。

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