“I Look in Your Eyes, Honey”: Internal Face Features Induce Spatial Frequency Preference for Human Face Processing

Numerous psychophysical experiments found that humans preferably rely on a narrow band of spatial frequencies for recognition of face identity. A recently conducted theoretical study by the author suggests that this frequency preference reflects an adaptation of the brain's face processing machinery to this specific stimulus class (i.e., faces). The purpose of the present study is to examine this property in greater detail and to specifically elucidate the implication of internal face features (i.e., eyes, mouth, and nose). To this end, I parameterized Gabor filters to match the spatial receptive field of contrast sensitive neurons in the primary visual cortex (simple and complex cells). Filter responses to a large number of face images were computed, aligned for internal face features, and response-equalized (“whitened”). The results demonstrate that the frequency preference is caused by internal face features. Thus, the psychophysically observed human frequency bias for face processing seems to be specifically caused by the intrinsic spatial frequency content of internal face features

'I Look in Your Eyes, Honey': Internal face features induce spatial frequency preference for human face processing

Numerous psychophysical experiments found that humans preferably rely on a narrow band of spatial frequencies for recognition of face identity. A recently conducted theoretical study by the author suggests that this frequency preference reflects an adaptation of the brain's face processing machinery to this specific stimulus class (i.e., faces). The purpose of the present study is to examine this property in greater detail and to specifically elucidate the implication of internal face features (i.e., eyes, mouth, and nose). To this end, I parameterized Gabor filters to match the spatial receptive field of contrast sensitive neurons in the primary visual cortex (simple and complex cells). Filter responses to a large number of face images were computed, aligned for internal face features, and response-equalized ("whitened"). The results demonstrate that the frequency preference is caused by internal face features. Thus, the psychophysically observed human frequency bias for face processing seems to be specifically caused by the intrinsic spatial frequency content of internal face features

'I Look in Your Eyes, Honey': Internal face features induce spatial frequency preference for human face processing

Numerous psychophysical experiments found that humans preferably rely on a narrow band of spatial frequencies for recognition of face identity. A recently conducted theoretical study by the author suggests that this frequency preference reflects an adaptation of the brain's face processing machinery to this specific stimulus class (i.e., faces). The purpose of the present study is to examine this property in greater detail and to specifically elucidate the implication of internal face features (i.e., eyes, mouth, and nose). To this end, I parameterized Gabor filters to match the spatial receptive field of contrast sensitive neurons in the primary visual cortex (simple and complex cells). Filter responses to a large number of face images were computed, aligned for internal face features, and response-equalized ("whitened"). The results demonstrate that the frequency preference is caused by internal face features. Thus, the psychophysically observed human frequency bias for face processing seems to be specifically caused by the intrinsic spatial frequency content of internal face features

Makeup Changes the Apparent Size of Facial Features

Makeup is a prominent example of the universal human practice of personal decoration. Many studies have shown that makeup makes the face appear more beautiful, but the visual cues mediating this effect are not well understood. A widespread belief holds that makeup makes the facial features appear larger. We tested this hypothesis using a novel reference comparison paradigm, in which carefully controlled photographs of faces with and without makeup were compared with an average reference face. Participants compared the relative size of specific features (eyebrows, eyes, nose, mouth) of the reference face and individual faces with or without makeup. Across three studies we found consistent evidence that eyes and eyebrows appeared larger with makeup than without. In contrast, there was almost no evidence that the lips appeared larger with makeup than without. In two studies using professionally applied makeup the nose appeared smaller with makeup than without, but in a study using self-applied makeup there was no difference. Thus makeup was found to alter the facial feature sizes in ways that are related to age and sex, two known factors of beauty. These results provide further evidence to support the idea that makeup functions in part by modifying biologically based factors of beauty

The role of low-level image features in the affective categorization of rapidly presented scenes

It remains unclear how the visual system is able to extract affective content from complex scenes even with extremely brief (\u3c 100 millisecond) exposures. One possibility, suggested by findings in machine vision, is that low-level features such as unlocalized, two-dimensional (2-D) Fourier spectra can be diagnostic of scene content. To determine whether Fourier image amplitude carries any information about the affective quality of scenes, we first validated the existence of image category differences through a support vector machine (SVM) model that was able to discriminate our intact aversive and neutral images with ~ 70% accuracy using amplitude-only features as inputs. This model allowed us to confirm that scenes belonging to different affective categories could be mathematically distinguished on the basis of amplitude spectra alone. The next question is whether these same features are also exploited by the human visual system. Subsequently, we tested observers’ rapid classification of affective and neutral naturalistic scenes, presented briefly (~33.3 ms) and backward masked with synthetic textures. We tested categorization accuracy across three distinct experimental conditions, using: (i) original images, (ii) images having their amplitude spectra swapped within a single affective image category (e.g., an aversive image whose amplitude spectrum has been swapped with another aversive image) or (iii) images having their amplitude spectra swapped between affective categories (e.g., an aversive image containing the amplitude spectrum of a neutral image). Despite its discriminative potential, the human visual system does not seem to use Fourier amplitude differences as the chief strategy for affectively categorizing scenes at a glance. The contribution of image amplitude to affective categorization is largely dependent on interactions with the phase spectrum, although it is impossible to completely rule out a residual role for unlocalized 2-D amplitude measures

Horizontal Information Drives the Behavioral Signatures of Face Processing

Recent psychophysical evidence indicates that the vertical arrangement of horizontal information is particularly important for encoding facial identity. In this paper we extend this notion to examine the role that information at different (particularly cardinal) orientations might play in a number of established phenomena each a behavioral “signature” of face processing. In particular we consider (a) the face inversion effect (FIE), (b) the facial identity after-effect, (c) face-matching across viewpoint, and (d) interactive, so-called holistic, processing of face parts. We report that filtering faces to remove all but the horizontal information largely preserves these effects but conversely, retaining vertical information generally diminishes or abolishes them. We conclude that preferential processing of horizontal information is a central feature of human face processing that supports many of the behavioral signatures of this critical visual operation