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The Effects of Blur and Inversion on the Recognition of Ambient Face Images

机译:模糊与反演对环境脸部图像识别的影响

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摘要

When viewing unfamiliar faces that vary in expressions, angles, and image quality, observers make many recognition errors. Specifically, in unconstrained identity-sorting tasks, observers struggle to cope with variation across different images of the same person while succeeding at telling different people apart. The use of ambient face images in this simple card-sorting task reveals the magnitude of these face recognition errors and suggests a useful platform to reexamine the nature of face processing using naturalistic stimuli. In the present study, we chose to investigate the impact of two basic stimulus manipulations (image blur and face inversion) on identity sorting with ambient images. Although these manipulations are both known to affect face processing when well-controlled, frontally viewed face images are used, examining how they affect performance for ambient images is an important step toward linking the large body of research using controlled face images to more ecologically valid viewing conditions. Briefly, we observed a high cost of image blur regardless of blur magnitude, and a strong inversion effect that affected observers' sensitivity to extrapersonal variability but did not affect the number of unique identities they estimated were present in the set of images presented to them.
机译:当观察在表达式,角度和图像质量时变化的不熟悉的面,观察者会产生许多识别错误。具体而言,在不受约束的身份分拣任务中,观察者努力应对同一个人的不同图像的变化,同时在讲述不同的人分开时。在这个简单的卡片排序任务中使用环境面部图像揭示了这些面部识别错误的大小,并建议使用自然刺激来重新审视面部处理的性质的有用平台。在本研究中,我们选择使用环境图像调查两个基本刺激操作(图像模糊和面部反转)对身份分类的影响。尽管已知这些操纵在受良好控制的情况下,所知的面部处理,但是使用正面观看的面部图像,检查它们如何影响环境图像的性能是将使用受控的面部图像连接到更生态的有效视图的大型研究的重要步骤状况。简而言之,我们观察到图像模糊的高成本,无论模糊数量,以及影响观察者对外部变异性的敏感性的强烈反转效果,但不影响他们估计的唯一身份的数量存在于所呈现给它们的图像集中。

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