Abstract
Previous work has shown mixed results regarding the role of different spatial frequency (SF) ranges in featural and configural processing of faces. Some studies suggest no special role of any given band for either type of processing, while others suggest that low SFs principally support configural analysis. Here we approach this issue by comparing human performance when making featural and configural discriminations to that of a model observer algorithm doing the same task. We find that human performance, measured in terms of accuracy, peaks at around 10 cycles/face regardless of whether featural or configural manipulations are being detected. We also find that accuracy peaks in the same part of the spectrum regardless of which feature is manipulated (i.e., eyes, nose, or mouth). Conversely, model observer performance, measured in terms of white noise tolerance, peaks at approximately 5 cycles/face, and this value again remains roughly constant regardless of the type of manipulation and feature manipulated. The ratio of the model's noise tolerance to a derived equivalent noise tolerance value for humans peaks around 10 cycles/face, similar to the accuracy data. These results provide evidence that the human performance maxima at 10 cycles/face are not due simply to the physical characteristics of face stimuli, but rather arise due to an interaction between available information and human perceptual processing.
Meeting abstract presented at VSS 2013