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Precise Ensemble Face Representation Given Incomplete Visual Input

机译:给定不完整的视觉输入即可进行精确的整体人脸表示

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Humans can recognize faces in the presence of environmental noise. Here, we explore whether ensemble perception of faces is similarly robust. Is summary statistical information available from crowds of faces that are visually incomplete? Observers viewed sets of faces varying in identity or expression and adjusted a test face to match the perceived average. In one condition, faces amodally completed behind horizontal bars. In another condition, identical facial information was presented, but in the foreground (i.e., face parts appeared on fragmented strips in front of a background). Baseline performance was determined by performance on sets of fully visible faces. The results revealed that the ensemble representation of amodally completing sets was significantly better than the fragmented sets and marginally worse than in the fully visible condition. These results suggest that some ensemble information is available given limited visual input and supports a growing body of work suggesting that ensembles may be represented in the absence of complete visual information.
机译:在存在环境噪声的情况下,人类可以识别人脸。在这里,我们探索对面孔的整体感知是否同样具有鲁棒性。是否可以从视觉不完整的人群中获得摘要统计信息?观察者查看了身份或表情各异的面孔集,并调整了测试面孔以匹配感知到的平均值。在一种情况下,单杠后的面无模态地完成。在另一种情况下,会呈现相同的面部信息,但是会呈现在前景中(即,面部出现在背景前面的碎片上)。基准性能取决于完全可见的面孔组的性能。结果表明,无模式完成集的集合表示明显好于碎片集,而在完全可见条件下则稍差。这些结果表明,在有限的视觉输入下,可以获得一些合奏信息,并且支持不断发展的工作,这表明在没有完整的视觉信息的情况下可以表示合奏。

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