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Finding Needles in Haystacks: Identity Mismatch Frequency and Facial Identity Verification

机译:在干草堆中寻找针头:身份不匹配频率和面部身份验证

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摘要

Accurate person identification is central to all security, police, and judicial systems. A commonplace method to achieve this is to compare a photo-ID and the face of its purported owner. The critical aspect of this task is to spot cases in which these two instances of a face do not match. Studies of person identification show that these instances often go undetected when mismatches occur regularly in an experiment, but this differs from everyday operations in which identity mismatches are rare. The current study therefore examined whether infrequent identity mismatches are more likely to go undetected by observers. In Experiments 1 and 2, identity mismatches were detected equally under low (2%) and high (50%) mismatch prevalence. This pattern persisted when viewing conditions were optimized for person identification in Experiment 3, by using a card-sorting task in which all face identities could be viewed repeatedly, and also under increased task difficulty, by constraining viewing conditions temporally in Experiment 4. These results imply that the infrequent occurrence of identity mismatches in security settings such as passport control does not impair an observer's ability to detect these important events.
机译:准确的人员识别对于所有安全,警察和司法系统至关重要。实现此目的的一种常见方法是比较一个带有照片的证件及其声称的拥有者的面孔。此任务的关键方面是找出面部的两个实例不匹配的情况。对人员识别的研究表明,在实验中经常发生不匹配的情况下,通常不会发现这些情况,但这与很少发生身份不匹配的日常操作不同。因此,当前的研究检查了观察者是否更经常发现身份不匹配的可能性。在实验1和2中,在低(2%)和高(50%)失配发生率下,均能检测到身份失配。在实验3中,通过使用卡片分类任务可以反复查看所有人的脸部身份,并且在任务难度增加的情况下,通过在实验4中暂时限制了观看条件,在实验3中优化了用于识别人的观看条件时,这种模式仍然存在。这意味着在诸如护照控制之类的安全设置中很少发生身份不匹配不会损害观察者检测这些重要事件的能力。

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