A novel, rapid, quantitative method for face discrimination

一种新型、快速、定量的面部识别方法

阅读:1

Abstract

Face discrimination ability has been widely studied in psychology, however a self-administered, adaptive method has not yet been developed. In this series of studies, we utilize Foraging Interactive D-prime (FInD) in conjunction with the Basel Face Model to quantify thresholds of face discrimination ability both in-lab and remotely. In Experiment 1, we measured sensitivity to changes for all 199 structural Principal Components of the Basel Face Model and found observers were most sensitive to the first 10 components, so we focused on these for the remaining studies. In Experiment 2, we remotely investigated how thresholds varied when one component changed, compared to when two components changed in combination. Thresholds measured remotely were not significantly different from those measured in-lab (t(14) = 0.23, p = .821), and thresholds were significantly lower for components in combination than alone (t(7) = 2.90, p = .023), consistent with probability summation and Euclidean distance between faces, but not superadditivity. In Experiment 3, we replicated Experiment 2 with slight rotation to the faces to prevent pointwise comparisons. Thresholds were higher with rotation (t(30) = 4.32, p < .001) and for single than combined components, but did not reach significance (t(7) = 2.24, p = .061). Charts were measured in approximately 25.90 ± 8.10 seconds.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。