The influence of natural contour and face size on the spatial frequency tuning for identifying upright and inverted faces.

It has previously been proposed that holistic face processing is based on low spatial frequencies (SFs) whereas featural processing relies on higher SFs, a hypothesis still widespread in the face processing literature today (e.g. Peters et al. in Eur J Neurosci 37(9):1448-1457, 2013). Since upright faces are supposedly recognized through holistic processing and inverted faces, using features, it is easy to take the leap to suggest a qualitatively different SF tuning for the identification of upright and vs. inverted faces. However, two independent studies (e.g. Gaspar et al. in Vision Res 48(28):2817-2826, 2008; Willenbockel et al. in J Exp Psychol Human 36(1):122-135, 2010a) found the same SF tuning for both stimulus presentations. Since these authors used relatively small faces hiding the natural facial contour, it is possible that differences in the SF tuning for identifying upright and inverted faces were missed. The present study thus revisits the SF tuning for upright and inverted faces face identification using the SF Bubbles technique. Our results still indicate that the same SFs are involved in both upright and inverted face recognition regardless of these additional parameters (contour and size), thus contrasting with previous data obtained using different methods (e.g. Oruc and Barton in J Vis 10(12):20, 1-12, 2010). The possible reasons subtending this divergence are discussed.

Efficient visual information for unfamiliar face matching despite viewpoint variations: It's not in the eyes!

Faces are encountered in highly diverse angles in real-world settings. Despite this considerable diversity, most individuals are able to easily recognize familiar faces. The vast majority of studies in the field of face recognition have nonetheless focused almost exclusively on frontal views of faces. Indeed, a number of authors have investigated the diagnostic facial features for the recognition of frontal views of faces previously encoded in this same view. However, the nature of the information useful for identity matching when the encoded face and test face differ in viewing angle remains mostly unexplored. The present study addresses this issue using individual differences and bubbles, a method that pinpoints the facial features effectively used in a visual categorization task. Our results indicate that the use of features located in the center of the face, the lower left portion of the nose area and the center of the mouth, are significantly associated with individual efficiency to generalize a face's identity across different viewpoints. However, as faces become more familiar, the reliance on this area decreases, while the diagnosticity of the eye region increases. This suggests that a certain distinction can be made between the visual mechanisms subtending viewpoint invariance and face recognition in the case of unfamiliar face identification. Our results further support the idea that the eye area may only come into play when the face stimulus is particularly familiar to the observer.