Tolerance of geometric distortions in infant's face recognition

Yamashita, Wakayo; Kanazawa, Susumu; Yamaguchi, Masami K.

doi:10.1016/j.infbeh.2013.10.003

Cited by 8 publications

(7 citation statements)

References 12 publications

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“…This was true not only for two-dimensional linear transformations, but also when the image was distorted by onedimensional linear transformations. These findings are consistent with previous studies, both in adults (Hole, 2002;Frowd et al 2014) and infants (Yamashita et al, 2013), as well as non-human primates (Taubert & Parr, 2011). However, when the face shape was changed by substantial non-linear transformation in Experiment 1, both accuracy and reaction times were attenuated.…”

Section: The Effect Of Linear and Non-linear Changes On Face Recognitionsupporting

confidence: 92%

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

et al. 2016

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Section: The Effect Of Linear and Non-linear Changes On Face Recognitionsupporting

confidence: 92%

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

et al. 2016

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“…Can this be explained as a learned ability, acquired through experience with printed images? Although this possibility is hard to definitively rule out, recent reports of infant and nonhuman primates' ability to recognize spatially distorted images reduce its likelihood ( Yamashita, Kanazawa, & Yamaguchi, 2014;Taubert & Parr, 2010). The asymmetry between the effects of horizontal and vertical within-axis distance ratios also challenges this idea.…”

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

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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.

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“…Although each child tested with a familiar teacher had known their teacher for a minimum of 3 months (with no difference in performance between children who had known their teacher for 3 versus 9 months), it is possible that children would show adult-like tolerance to variability for their caregiver's face due to children's early advantage with these faces. Newborn infants show a preference for their mother's face (Pascalis, De Schonen, Morton, Deruelle, & Fabre-Grenet, 1995;Bushnell, 2001), and older infants show adult-like patterns of recognition for their mother's face, such as recognition despite geometric distortions (Yamashita, Kanazawa & Yamaguchi, 2014) and masking of external features (Bartrip, Morton, & de Schonen, 2001), as well as inversion effects (Balas et al 2009). In short, representations for caregivers might be more robust than for other familiar faces due to them being highly overlearned (Tong & Nakayama, 1999).…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

That’s my teacher! Children’s ability to recognize personally familiar and unfamiliar faces improves with age

Laurence

Mondloch

2016

Journal of Experimental Child Psychology

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Most previous research on the development of face recognition has focused on recognition of highly controlled images. One of the biggest challenges of face recognition is to identify an individual across images that capture natural variability in appearance. We created a child-friendly version of Jenkins, White, Van Montford, and Burton's sorting task (Cognition, 2011, Vol. 121, pp. 313-323) to investigate children's recognition of personally familiar and unfamiliar faces. Children between 4 and 12years of age were presented with a familiar/unfamiliar teacher's house and a pile of face photographs (nine pictures each of the teacher and another identity). Each child was asked to put all the pictures of the teacher inside the house while keeping the other identity out. Children over 6years of age showed adult-like familiar face recognition. Unfamiliar face recognition improved across the entire age range, with considerable variability in children's performance. These findings suggest that children's ability to tolerate within-person variability improves with age and support a face-space framework in which faces are represented as regions, the size of which increases with age.

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Tolerance of geometric distortions in infant's face recognition

Cited by 8 publications

References 12 publications

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

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

Recognizing Facial Slivers

That’s my teacher! Children’s ability to recognize personally familiar and unfamiliar faces improves with age

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