Configural relations and a critical band of spatial frequencies (SFs) in the middle range are particularly important for face recognition. We report the results of four experiments in which the relationship between these two types of information was examined. In Experiments 1, 2A, and 2B, the face inversion effect (FIE) was used to probe configural face encoding. Recognition of upright and inverted faces and nonface objects was measured in four conditions: a no-filter condition and three SF conditions (low, medium, and high frequency). We found significant FIEs of comparable magnitudes for all frequency conditions. In Experiment 3, discrimination of faces on the basis of either configural or featural modifications was measured under the same four conditions. Although the ability to discriminate configural modifications was superior in the medium-frequency condition, so was the ability to discriminate featural modifications. We conclude that the band of SF that is critical for face recognition does not contribute preferentially to configural encoding.

The effects of spatial frequency overlap between pairs of low-pass versus high-pass images on face recognition and matching were examined in 6 experiments. Overlap was defined as the range of spatial frequencies shared by a pair of filtered images. This factor was manipulated by processing image pairs with high-pass/low-pass filter pairs whose 50% cutoff points varied in their separation from one another. The effects of the center frequency of filter pairs were also investigated. In general, performance improved with greater overlap and higher center frequency. In control conditions, the image pairs were processed with identical filters and thus had complete overlap. Even severely filtered low-pass or high-pass images in these conditions produced superior performance. These results suggest that face recognition is more strongly affected by spatial frequency overlap than by the frequency content of the images.

No abstract

Previous studies have suggested that face identification is more sensitive to variations in spatial frequency content than object recognition, but none have compared how sensitive the 2 processes are to variations in spatial frequency overlap (SFO). The authors tested face and object matching accuracy under varying SFO conditions. Their results showed that object recognition was more robust to SFO variations than face recognition and that the vulnerability of faces was not due to reliance on configural processing. They suggest that variations in sensitivity to SFO help explain the vulnerability of face recognition to changes in image format and the lack of a middle-frequency advantage in object recognition.

No abstract