Costen N P, Parker D M, Craw I
University of Aberdeen, Scotland.
Percept Psychophys. 1996 May;58(4):602-12. doi: 10.3758/bf03213093.
If face images are degraded by block averaging, there is a nonlinear decline in recognition accuracy as block size increases, suggesting that identification requires a critical minimum range of object spatial frequencies. The identification of faces was measured with equivalent Fourier low-pass filtering and block averaging preserving the same information and with high-pass transformations. In Experiment 1, accuracy declined and response time increased in a significant nonlinear manner in all cases as the spatial-frequency range was reduced. However, it did so at a faster rate for the quantized and high-passed images. A second experiment controlled for the differences in the contrast of the high-pass faces and found a reduced but significant and nonlinear decline in performance as the spatial-frequency range was reduced. These data suggest that face identification is preferentially supported by a band of spatial frequencies of approximately 8-16 cycles per face; contrast or line-based explanations were found to be inadequate. The data are discussed in terms of current models of face identification.
如果面部图像因分块平均而退化，那么随着块大小的增加，识别准确率会呈非线性下降，这表明识别需要物体空间频率的一个关键最小范围。使用等效傅里叶低通滤波、保留相同信息的分块平均以及高通变换来测量面部识别。在实验1中，随着空间频率范围的减小，在所有情况下准确率均显著非线性下降，反应时间增加。然而，对于量化图像和高通图像，下降速度更快。第二个实验控制了高通面部对比度的差异，发现随着空间频率范围的减小，性能下降但仍显著且呈非线性。这些数据表明，面部识别优先受到每面部约8 - 16个周期的空间频率带的支持；基于对比度或线条的解释被发现是不充分的。根据当前的面部识别模型对这些数据进行了讨论。
