Coarse-to-Fine(r) Automatic Familiar Face Recognition in the Human Brain

2021 ◽  
Author(s):  
Xiaoqian Yan ◽  
Valérie Goffaux ◽  
Bruno Rossion
Keyword(s):  
Face Recognition ◽  
Human Brain ◽  
Spatial Resolution ◽  
Predictive Coding ◽  
Head Width ◽  
Familiar Face ◽  
Visual Inputs ◽  
Electroencephalogram Eeg ◽  
Coarse To Fine ◽  
Unfamiliar Faces

Abstract At what level of spatial resolution can the human brain recognize a familiar face in a crowd of strangers? Does it depend on whether one approaches or rather moves back from the crowd? To answer these questions, 16 observers viewed different unsegmented images of unfamiliar faces alternating at 6 Hz, with spatial frequency (SF) content progressively increasing (i.e., coarse-to-fine) or decreasing (fine-to-coarse) in different sequences. Variable natural images of celebrity faces every sixth stimulus generated an objective neural index of single-glanced automatic familiar face recognition (FFR) at 1 Hz in participants’ electroencephalogram (EEG). For blurry images increasing in spatial resolution, the neural FFR response over occipitotemporal regions emerged abruptly with additional cues at about 6.3–8.7 cycles/head width, immediately reaching amplitude saturation. When the same images progressively decreased in resolution, the FFR response disappeared already below 12 cycles/head width, thus providing no support for a predictive coding hypothesis. Overall, these observations indicate that rapid automatic recognition of heterogenous natural views of familiar faces is achieved from coarser visual inputs than generally thought, and support a coarse-to-fine FFR dynamics in the human brain.

Self- or familiar-face recognition advantage? New insight using ambient images

2018 ◽  
Vol 71 (6) ◽  
pp. 1396-1404 ◽  
Author(s):  
Catherine Bortolon ◽  
Siméon Lorieux ◽  
Stéphane Raffard
Keyword(s):  
Face Recognition ◽  
Graduate Students ◽  
Matching Task ◽  
Healthy Individuals ◽  
Familiarity Effect ◽  
Familiar Face ◽  
The Past ◽  
The Face ◽  
First Time ◽  
Unfamiliar Faces

Self-face recognition has been widely explored in the past few years. Nevertheless, the current literature relies on the use of standardized photographs which do not represent daily-life face recognition. Therefore, we aim for the first time to evaluate self-face processing in healthy individuals using natural/ambient images which contain variations in the environment and in the face itself. In total, 40 undergraduate and graduate students performed a forced delayed-matching task, including images of one’s own face, friend, famous and unknown individuals. For both reaction time and accuracy, results showed that participants were faster and more accurate when matching different images of their own face compared to both famous and unfamiliar faces. Nevertheless, no significant differences were found between self-face and friend-face and between friend-face and famous-face. They were also faster and more accurate when matching friend and famous faces compared to unfamiliar faces. Our results suggest that faster and more accurate responses to self-face might be better explained by a familiarity effect – that is, (1) the result of frequent exposition to one’s own image through mirror and photos, (2) a more robust mental representation of one’s own face and (3) strong face recognition units as for other familiar faces.

scholarly journals How Familiarity Warps Representation in Face Space

2018 ◽  
Author(s):  
Vassiki Chauhan ◽  
M. Ida Gobbini
Keyword(s):  
Face Recognition ◽  
Structural Features ◽  
Image Distortion ◽  
Face Space ◽  
Familiar Face ◽  
Unfamiliar Faces

AbstractRecognition of familiar as compared to unfamiliar faces is robust and resistant to marked image distortion or degradation. Here we tested the flexibility of familiar face recognition with a morphing paradigm where the appearance of a personally familiar face was mixed with the appearance of a stranger. The aim was to assess how categorical boundaries for recognition of identity are affected by familiarity. We found a narrower categorical boundary for the identity of personally familiar faces when they were mixed with unfamiliar identities as compared to the control condition, in which the appearance of two unfamiliar faces were mixed. Our results suggest that familiarity warps the representational geometry of face space, amplifying perceptual distances for small changes in the appearance of familiar faces that are inconsistent with the structural features that define their identities.

scholarly journals Critical Features for Face Recognition

2018 ◽  
Author(s):  
Naphtali Abudarham ◽  
Lior Shkiller ◽  
Galit Yovel
Keyword(s):  
Neural Network ◽  
Face Recognition ◽  
Deep Neural Network ◽  
Recognition Algorithm ◽  
Facial Features ◽  
Perceptual Representation ◽  
Familiar Face ◽  
Perceptual Representations ◽  
Unfamiliar Faces ◽  
New Framework

Face recognition is a computationally challenging task that humans perform effortlessly. Nonetheless, this remarkable ability is limited to familiar faces and does not generalize to unfamiliar faces. To account for humans’ superior ability to recognize familiar faces, current theories suggest that familiar and unfamiliar faces have different perceptual representations. In the current study, we applied a reverse engineering approach to reveal which facial features are critical for familiar face recognition. In contrast to current views, we discovered that the same subset of features that are used for matching unfamiliar faces, are also used for matching as well as recognition of familiar faces. We further show that these features are also used by a deep neural network face recognition algorithm. We therefore propose a new framework that assumes similar perceptual representation for all faces and integrates cognition and perception to account for humans’ superior recognition of familiar faces.

scholarly journals How robust is familiar face recognition? A repeat detection study of more than 1000 faces

2018 ◽  
Vol 5 (5) ◽  
pp. 170634
Author(s):  
Angus F. Chapman ◽  
Hannah Hawkins-Elder ◽  
Tirta Susilo
Keyword(s):  
Face Recognition ◽  
Detection Task ◽  
Familiar Face ◽  
Robust Representation ◽  
Face Images ◽  
Unfamiliar Face ◽  
Unfamiliar Faces ◽  
Repeat Detection ◽  
Better Than

Recent theories suggest that familiar faces have a robust representation in memory because they have been encountered over a wide variety of contexts and image changes (e.g. lighting, viewpoint and expression). By contrast, unfamiliar faces are encountered only once, and so they do not benefit from such richness of experience and are represented based on image-specific details. In this registered report, we used a repeat detection task to test whether familiar faces are recognized better than unfamiliar faces across image changes. Participants viewed a stream of more than 1000 celebrity face images for 0.5 s each, any of which might be repeated at a later point and has to be detected. Some participants saw the same image at repeats, while others saw a different image of the same face. A post-experimental familiarity check allowed us to determine which celebrities were and were not familiar to each participant. We had three predictions: (i) detection would be better for familiar than unfamiliar faces, (ii) detection would be better across same rather than different images, and (iii) detection of familiar faces would be comparable across same and different images, but detection of unfamiliar faces would be poorer across different images. We obtained support for the first two predictions but not the last. Instead, we found that repeat detection of faces, regardless of familiarity, was poorer across different images. Our study suggests that the robustness of familiar face recognition may have limits, and that under some conditions, familiar face recognition can be just as influenced by image changes as unfamiliar face recognition.

scholarly journals An objective, sensitive and ecologically valid neural measure of rapid human individual face recognition

2019 ◽  
Vol 6 (6) ◽  
pp. 181904 ◽  
Author(s):  
Friederike G. S. Zimmermann ◽  
Xiaoqian Yan ◽  
Bruno Rossion
Keyword(s):  
Face Recognition ◽  
Visual Stimulation ◽  
Natural Images ◽  
Neural Basis ◽  
Face Identity ◽  
Familiar Face ◽  
Recognition Response ◽  
Human Individual ◽  
The Individual ◽  
Unfamiliar Faces

Humans may be the only species able to rapidly and automatically recognize a familiar face identity in a crowd of unfamiliar faces, an important social skill. Here, by combining electroencephalography (EEG) and fast periodic visual stimulation (FPVS), we introduce an ecologically valid, objective and sensitive neural measure of this human individual face recognition function. Natural images of various unfamiliar faces are presented at a fast rate of 6 Hz, allowing one fixation per face, with variable natural images of a highly familiar face identity, a celebrity, appearing every seven images (0.86 Hz). Following a few minutes of stimulation, a high signal-to-noise ratio neural response reflecting the generalized discrimination of the familiar face identity from unfamiliar faces is observed over the occipito-temporal cortex at 0.86 Hz and harmonics. When face images are presented upside-down, the individual familiar face recognition response is negligible, being reduced by a factor of 5 over occipito-temporal regions. Differences in the magnitude of the individual face recognition response across different familiar face identities suggest that factors such as exposure, within-person variability and distinctiveness mediate this response. Our findings of a biological marker for fast and automatic recognition of individual familiar faces with ecological stimuli open an avenue for understanding this function, its development and neural basis in neurotypical individual brains along with its pathology. This should also have implications for the use of facial recognition measures in forensic science.

scholarly journals Compressed representation of natural image variability underlies high accuracy in face recognition

2021 ◽  
Author(s):  
David White ◽  
Tanya Wayne ◽  
Victor Perrone de Lima Varela
Keyword(s):  
Face Recognition ◽  
Computational Analysis ◽  
High Accuracy ◽  
Natural Image ◽  
Cognitive Representations ◽  
Human Face Recognition ◽  
Familiar Face ◽  
Similarity Ratings ◽  
Image Averaging ◽  
Unfamiliar Faces

Accurately recognising faces is fundamental to human social interaction. In recent years it has become clear that people’s accuracy differs markedly depending on viewer’s familiarity with a face and their individual skill, but the cognitive and neural bases of these accuracy differences are not understood. We examined cognitive representations underlying these accuracy differences by measuring similarity ratings to natural facial image variation. Using image averaging, and inspired by the computation of Analysis of Variance, we partitioned image variation into differences between faces (between-identity variation) and differences between photos of the same face (within-identity variation). Contrary to prevailing accounts of human face recognition and perceptual learning, we found that modulation of within-identity variation – rather than between-identity variation – was associated with high accuracy. First, similarity of within-identity variation was compressed for familiar faces relative to unfamiliar faces. Second, viewers that are extremely accurate in face recognition – ‘super-recognisers’ – showed enhanced compression of within-identity variation that was most marked for familiar faces. We also present computational analysis showing that cognitive transformations of between- and within-identity variation make separable contributions to perceptual expertise in unfamiliar and familiar face identification respectively. We conclude that inter- and intra-individual accuracy differences primarily arise from differences in the representation of familiar face image variation.

scholarly journals Recognizing Faces

2017 ◽  
Vol 26 (3) ◽  
pp. 212-217 ◽  
Author(s):  
Andrew W. Young ◽  
A. Mike Burton
Keyword(s):  
Face Recognition ◽  
Everyday Life ◽  
Real Life ◽  
Research Literature ◽  
Familiar Face ◽  
Image Variability ◽  
Unfamiliar Faces

The idea that most of us are good at recognizing faces permeates everyday thinking and is widely used in the research literature. However, it is a correct characterization only of familiar-face recognition. In contrast, the perception and recognition of unfamiliar faces can be surprisingly error-prone, and this has important consequences in many real-life settings. We emphasize the variability in views of faces encountered in everyday life and point out how neglect of this important property has generated some misleading conclusions. Many approaches have treated image variability as unwanted noise, whereas we show how studies that use and explore the implications of image variability can drive substantial theoretical advances.

scholarly journals Perceptual difficulty modulates the direction of information flow in familiar face recognition

2020 ◽  
Author(s):  
Hamid Karimi-Rouzbahani ◽  
Farzad Remezani ◽  
Alexandra Woolgar ◽  
Anina Rich ◽  
Masoud Ghodrati
Keyword(s):  
Face Recognition ◽  
Neural Representation ◽  
Neural Correlate ◽  
Familiar Face ◽  
Frontal Brain ◽  
Neurophysiological Studies ◽  
Perceptual Difficulty ◽  
Sensory Evidence ◽  
The Brain ◽  
Unfamiliar Faces

AbstractHumans are fast and accurate when they recognize familiar faces. Previous neurophysiological studies have shown enhanced representations for the dichotomy of familiar vs. unfamiliar faces. As familiarity is a spectrum, however, any neural correlate should reflect graded representations for more vs. less familiar faces along the spectrum. By systematically varying familiarity across stimuli, we show a neural familiarity spectrum using electroencephalography. We then evaluated the spatiotemporal dynamics of familiar face recognition across the brain. Specifically, we developed a novel informational connectivity method to test whether peri-frontal brain areas contribute to familiar face recognition. Results showed that feed-forward flow dominates for the most familiar faces and top-down flow was only dominant when sensory evidence was insufficient to support face recognition. These results demonstrate that perceptual difficulty and the level of familiarity influence the neural representation of familiar faces and the degree to which peri-frontal neural networks contribute to familiar face recognition.

Familiarity of Faces: Sense or Feeling?

2015 ◽  
Vol 29 (1) ◽  
pp. 20-25 ◽  
Author(s):  
Paola Bonifacci ◽  
Lorenzo Desideri ◽  
Cristina Ottaviani
Keyword(s):  
Face Recognition ◽  
Eye Movements ◽  
Skin Conductance ◽  
Electrodermal Activity ◽  
Adaptive Process ◽  
Familiar Face ◽  
Skin Conductance Responses ◽  
Exploratory Investigation ◽  
Novel Approaches ◽  
Unfamiliar Faces

Where does the experience of familiarity come from? Is it the same as sensory perception? Two novel approaches were combined to investigate the highly adaptive process of familiar face recognition: the inclusion of friends and family members as personally familiar faces and measures of eye movements and skin conductance responses (SCR). A sample of 16 university students was asked to look at photographs of 8 personally familiar faces (friends and relatives) and 8 unfamiliar faces. From the analysis of eye movement patterns, a preference for internal features (mouth, eyes, nose) for both familiar and unfamiliar faces emerged and a significant increase in electrodermal activity was found for personally familiar compared to unfamiliar faces. Higher SCR recovery values were found in response to friends. Findings from this exploratory investigation suggest that familiar faces are not looked at in a special way; instead we “feel” a sense of familiarity that comes and goes faster for relatives than for close friends.

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