Face-selective regions show invariance to linear, but not to non-linear, changes in facial images

Baseler, Heidi A.; Young, Andrew W.; Jenkins, Rob; Burton, A. Mike; Andrews, Timothy J.

doi:10.1016/j.neuropsychologia.2016.10.004

Cited by 8 publications

(11 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A configural account of face recognition suggests encoded interfeature metric distances are important for successful recognition of people we know (Richler et al, 2009), but often, as observed in our experiments, faces are presented under relatively optimal viewing conditions, whereby faces are placed in a twodimensional picture plane facing front-on. When presented in this way, our results add to a body of literature that highlights limits to the explanatory power of configuration in recognition of familiar faces (e.g., Baseler et al, 2016;Bindemann et al, 2008;Hole et al, 2002;Noyes & Jenkins, 2017;Sandford et al, 2018). Therefore, we expect configuration will not be helpful in recognition of faces with varying appearances across different images of the same person, but future research is needed to explore whether accounts based on configuration and variability in appearance can be reconciled (e.g., whether interfeature distances and ratio of distances contribute to learning and recognition from varying images).…”

Section: Discussionsupporting

confidence: 62%

“…Effects of nonglobal stretching, to the best of our knowledge, have been reported only in studies that set out to understand familiar face recognition (Baseler, Young, Jenkins, Burton, & Andrews, 2016; Hole et al., 2002). We also focused on recognition of familiar faces indexed by familiarity categorization by presenting famous and nonfamous faces.…”

Section: Methodsmentioning

confidence: 95%

See 1 more Smart Citation

Recognition of Deformed Familiar Faces: Contrast Negation and Nonglobal Stretching

Sandford

Rego

2019

Perception

View full text Add to dashboard Cite

Familiar face recognition is robust to subtle and drastic changes in appearance. Knowing which conditions harm our recognition highlights underlying processes that have prominent roles in face learning. Here, we focused on two image deformations that studies suggest independently harm recognition: contrast negation and stretching of top or bottom halves of a face orthogonal to the unstretched half (nonglobal stretching). Participants were asked to categorize self-reported familiar or unfamiliar faces presented in photographic positive and negative in a fully within-subjects design. In Experiments 1 and 2, recognition of contrast-positive faces was robust to global and nonglobal stretching, suggesting iso-dimension ratios do not have a role in familiar face recognition. However, performance was consistently impaired by contrast negation in all configurational conditions. Further reductions in categorization accuracy when top halves of contrast-negated faces are stretched suggest some limited role for configuration under these image conditions. In Experiment 3, presenting the top or bottom half of nonglobal stretch conditions suggested categorization of nonglobal stretch faces did not require perception of the whole face, in the research design reported here. These results highlight further limits to configurational accounts of face recognition and indicate a relatively important role for surface reflectance cues.

show abstract

Section: Discussionsupporting

confidence: 62%

Section: Methodsmentioning

confidence: 95%

Recognition of Deformed Familiar Faces: Contrast Negation and Nonglobal Stretching

Sandford

Rego

2019

Perception

View full text Add to dashboard Cite

show abstract

“…In fact, Todorov and Oosterhof (2011) directly compared the performance of linear and nonlinear (quadratic) models and showed only limited improvement in the amount of variance explained by a quadratic model. In this respect, it is interesting that fMRI studies have shown that face-responsive brain regions also track relatively linear changes in face properties (Baseler, Young, Jenkins, Burton & Andrews, 2016). In making this point, we are not however seeking to claim that the human brain uses PCA as such -the point is only that PCA offers a useful way of demonstrating the presence of information that the brain can exploit.…”

Section: Discussionmentioning

confidence: 99%

Understanding facial impressions between and within identities

2019

Self Cite

View full text Add to dashboard Cite

A paradoxical finding from recent studies of face perception is that observers are error-prone and inconsistent when judging the identity of unfamiliar faces, but nevertheless reasonably consistent when judging traits. Our aim is to understand this difference. Using everyday ambient images of faces, we show that visual image statistics can predict observers' consensual impressions of trustworthiness, attractiveness and dominance, which represent key dimensions of evaluation in leading theoretical accounts of trait judgement. In Study 1, image statistics derived from ambient images of multiple face identities were able to account for 51% of the variance in consensual impressions of entirely novel ambient images. Shape properties were more effective predictors than surface properties, but a combination of both achieved the best results. In Study 2 and Study 3, statistics derived from multiple images of a particular face achieved the best generalisation to new images of that face, but there was nonetheless significant generalisation between images of the faces of different individuals. Hence, whereas idiosyncratic variability across different images of the same face is sufficient to cause substantial problems in judging the identities of unfamiliar faces, there are consistencies between faces which are sufficient to support (to some extent) consensual trait judgements. Furthermore, much of this consistency can be captured in simple operational models based on image statistics. Facial impressions 3 Facial impressions 4 surprisingly wide range of performance across different observers in the normal population (Burton, White & McNeill, 2010). By analysing the statistical properties of ambient images of faces, Burton, Kramer, Ritchie and Jenkins (2016) showed that image variability is to some extent idiosyncratic-that is, the ways in which one person's face varies across images can be different for someone else's face. Learning to recognise a familiar face thus involves learning how that face can vary, through seeing it in many settings-in effect becoming sufficiently expert with that face identity to be able to recognise new photos of the same person. But this form of perceptual expertise is identity-specific and may not generalise to another person's face, because that face varies in different ways. For this reason, unfamiliar face recognition is often poor because the range of variability of an unfamiliar face is unknown (Burton et al., 2016; Kramer, Young & Burton, 2018; Young & Burton, 2018). Computational work has shown the utility of this approach by simulating a range of well-known properties of familiar and unfamiliar face recognition (Kramer, Young, Day & Burton, 2017; Kramer et al., 2018). Although perception of the identities of unfamiliar faces can be problematic, many other characteristics are more easily seen. These include relatively objective properties determined by structural cues such as apparent gender, age and ethnicity (Bruce & Young, 2012) and more subjective impressions of social dispositions su...

show abstract

“…Similarly, a recent fMRI decoding study found a similarly organized view-invariant face identity representation pathway in the human visual system that begins in early visual cortex and the occipital face area (OFA) with a representation of head view that is invariant to identity; proceeds to an intermediate level of representation in the face fusiform area (FFA), which represents identity entangled with head view; and culminates in the right inferior frontal cortex face area with a 3-D view-invariant representation of identity (Guntupalli, Wheeler, & Gobbini, 2017). Although currently no data exist to classify which of these areas support configural face processing, a recently published study found that the OFA and FFA are invariant to slight linear distortions, but not to nonlinear distortions (Baseler, Young, Jenkins, Mike Burton, & Andrews, 2016). This finding may initially seem counter to what our theory would predict.…”

Section: Compressed Faces As An Epiphenomenon Of Tolerance To Depth Rmentioning

confidence: 99%

Recognizing Facial Slivers

Gilad-Gutnick

Harmatz

Tsourides

et al. 2018

Journal of Cognitive Neuroscience

View full text Add to dashboard Cite

We report here an unexpectedly robust ability of healthy human individuals ( n = 40) to recognize extremely distorted needle-like facial images, challenging the well-entrenched notion that veridical spatial configuration is necessary for extracting facial identity. In face identification tasks of parametrically compressed internal and external features, we found that the sum of performances on each cue falls significantly short of performance on full faces, despite the equal visual information available from both measures (with full faces essentially being a superposition of internal and external features). We hypothesize that this large deficit stems from the use of positional information about how the internal features are positioned relative to the external features. To test this, we systematically changed the relations between internal and external features and found preferential encoding of vertical but not horizontal spatial relationships in facial representations ( n = 20). Finally, we employ magnetoencephalography imaging ( n = 20) to demonstrate a close mapping between the behavioral psychometric curve and the amplitude of the M250 face familiarity, but not M170 face-sensitive evoked response field component, providing evidence that the M250 can be modulated by faces that are perceptually identifiable, irrespective of extreme distortions to the face's veridical configuration. We theorize that the tolerance to compressive distortions has evolved from the need to recognize faces across varying viewpoints. Our findings help clarify the important, but poorly defined, concept of facial configuration and also enable an association between behavioral performance and previously reported neural correlates of face perception.

show abstract

Face-selective regions show invariance to linear, but not to non-linear, changes in facial images

Cited by 8 publications

References 48 publications

Recognition of Deformed Familiar Faces: Contrast Negation and Nonglobal Stretching

Recognition of Deformed Familiar Faces: Contrast Negation and Nonglobal Stretching

Understanding facial impressions between and within identities

Recognizing Facial Slivers

Contact Info

Product

Resources

About