Does face inversion change spatial frequency tuning?

Willenbockel, Verena; Fiset, Daniel; Chauvin, Alan; Blais, Caroline; Arguin, Martin; Tanaka, James W.; Bub, Daniel N.; Gosselin, Frédéric

doi:10.1037/a0016465

Cited by 62 publications

(117 citation statements)

References 81 publications

(182 reference statements)

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“…For example, two studies examined the spatial frequency bands used for face identification and found no differences between the upright and inverted conditions (Gaspar, Sekuler, & Bennett, 2008;Willenbockel et al, 2010). Also inconsistent with the holistic processing hypothesis, Gold, Mundy, and Tjan (2012) have shown that human observers' ability to identify a whole face is not superior to what is predicted by an optimal linear integration of information from individual features.…”

Section: Introductionmentioning

confidence: 93%

Size determines whether specialized expert processes are engaged for recognition of faces

2014

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Many influential models of face recognition postulate specialized expert processes that are engaged when viewing upright, own-race faces, as opposed to a general-purpose recognition route used for nonface objects and inverted or other-race faces. In contrast, others have argued that empirical differences do not stem from qualitatively distinct processing. We offer a potential resolution to this ongoing controversy. We hypothesize that faces engage specialized processes at large sizes only. To test this, we measured recognitionefficiencies fora widerange of sizes.Uprightface recognition efficiency increased with size. This was not due to better visibility of basic image features at large sizes. We ensured this bycalculating efficiency relative to a specialized ideal observer unique to each individual that incorporated size-related changes in visibility and by measuring inverted efficiencies acrossthe same range of face sizes. Inverted face recognition efficiencies did not change with size. A qualitative face inversion effect, defined as the ratio of relative upright and inverted efficiencies, showed a complete lack of inversion effects for small sizes up to 68. In contrast, significant face inversion effects were found for all larger sizes. Size effects may stem from predominance of larger faces in the overall exposure to faces, which occur at closer viewing distances typical of social interaction. Our results offer a potential explanation for the contradictory findings in the literature regarding the special status offaces.

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Section: Introductionmentioning

confidence: 93%

Size determines whether specialized expert processes are engaged for recognition of faces

2014

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“…Gold et al, 1999;Näsänen, 1999;Willenbockel et al, 2010). Even more surprising, although face inversion profoundly disrupts low-SF-driven interactive face processing, several papers report that the magnitude of the FIE is equal across SF (Boutet et al, 2003;Gaspar et al, 2008a;Goffaux, 2008;Willenbockel et al, 2010). This divergent empirical evidence has led researchers to question the role of interactive face processing in face recognition (Konar et al, 2010).…”

Section: Acknowledgmentsmentioning

confidence: 99%

“…Goffaux, 2009) does not coincide with SF best supporting the recognition of face identity (between 7 and 16 cpf; e.g. Gold et al, 1999;Näsänen, 1999;Willenbockel et al, 2010). Even more surprising, although face inversion profoundly disrupts low-SF-driven interactive face processing, several papers report that the magnitude of the FIE is equal across SF (Boutet et al, 2003;Gaspar et al, 2008a;Goffaux, 2008;Willenbockel et al, 2010).…”

Section: Acknowledgmentsmentioning

confidence: 99%

“…To our knowledge, this is the first time that the FIE has been related to a disruption in processing of a single visual component of faces. (Gaspar et al, 2008a(Gaspar et al, , 2008bWillenbockel et al, 2010).…”

Section: Data Analysesmentioning

confidence: 99%

“…The mean luminance value was subtracted from every image. Filtered stimuli were generated by Fast Fourier transforming the original image using Matlab 7.0.1 and multiplying the Fourier energy with orientation filters: these allowed all SFs to pass but had a wrapped Gaussian energy profiles in the orientation domain, centered on one orientation with a particular bandwidth specified band of intermediate SFs (7-16 cycles per face, cpf; Costen et al, 1994Costen et al, , 1996Gold et al, 1999;Näsänen, 1999;Willenbockel et al, 2010). In contrast, the coarse structure provided by low SFs contributes to both the processing of holistic facial information (interactive feature processing) and the perception of fearful expressions (Collishaw and Hole, 2000;Goffaux et al, 2003Goffaux et al, , 2005Goffaux and Rossion, 2006;Goffaux, 2009;Vlamings et al, 2009).…”

Section: Stimulimentioning

confidence: 99%

See 2 more Smart Citations

Horizontal information drives the behavioural signatures of face processing

Goffaux¹

2010

Front. Psychology

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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.

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

Royer

Willenbockel

Blais

et al. 2016

Psychological Research

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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.

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Does face inversion change spatial frequency tuning?

Cited by 62 publications

References 81 publications

Size determines whether specialized expert processes are engaged for recognition of faces

Size determines whether specialized expert processes are engaged for recognition of faces

Horizontal information drives the behavioural signatures of face processing

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

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