scholarly journals Characterizing developmental prosopagnosia beyond face perception: Impaired recollection but intact familiarity recognition

2020 ◽  
Author(s):  
Anna Stumps ◽  
Elyana Saad ◽  
David Rothlein ◽  
Mieke Verfaellie ◽  
Joseph DeGutis
Keyword(s):  
Face Recognition ◽  
Face Perception ◽  
Roc Analysis ◽  
Recognition Task ◽  
High Confidence ◽  
Perceptual Deficit ◽  
Model Based ◽  
Confidence Ratings

Converging lines of research suggests that many developmental prosopagnosics (DPs) have impairments beyond face perception, but currently no framework exists to characterize these impaired mechanisms. One potential extra-perceptual deficit is that DPs encode/retrieve faces in a distinct manner from controls that does not sufficiently support individuation. To test this possibility, 30 DPs and 30 matched controls performed an old/new face recognition task while providing confidence ratings, to which a model-based ROC analysis was applied. DPs had significantly reduced recollection compared to controls, driven by fewer ‘high-confidence target’ responses, but intact familiarity. Recollection and face perception ability uniquely predicted objective and subjective prosopagnosia symptoms, together explaining 51% and 56% of the variance, respectively. These results suggest that a specific deficit in face recollection in DP may represent a core aspect of the difficulty in confidently identifying an individual by their face.

High confidence in falsely recognizing prototypical faces

2018 ◽  
Vol 71 (6) ◽  
pp. 1348-1356 ◽  
Author(s):  
Cristina Sampaio ◽  
Victoria Reinke ◽  
Jeffrey Mathews ◽  
Alexandra Swart ◽  
Stephen Wallinger
Keyword(s):  
Face Recognition ◽  
Multiple Choice ◽  
Recognition Task ◽  
Choice Task ◽  
High Rate ◽  
False Alarms ◽  
High Confidence ◽  
Accuracy Relationship

We applied a metacognitive approach to investigate confidence in recognition of prototypical faces. Participants were presented with sets of faces constructed digitally as deviations from prototype/base faces. Participants were then tested with a simple recognition task (Experiment 1) or a multiple-choice task (Experiment 2) for old and new items plus new prototypes, and they showed a high rate of confident false alarms to the prototypes. Confidence and accuracy relationship in this face recognition paradigm was found to be positive for standard items but negative for the prototypes; thus, it was contingent on the nature of the items used. The data have implications for lineups that employ match-to-suspect strategies.

scholarly journals DeepWTPCA-L1: A New Deep Face Recognition Model Based on WTPCA-L1 Norm Features

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 65091-65100
Author(s):  
Ayyad Maafiri ◽  
Omar Elharrouss ◽  
Saad Rfifi ◽  
Somaya Ali Al-Maadeed ◽  
Khalid Chougdali
Keyword(s):  
Face Recognition ◽  
L1 Norm ◽  
Recognition Model ◽  
Model Based

The effect of interpersonal multisensory stimulation on the self-face recognition in adults with autistic syndrome disorder

2016 ◽  
Vol 33 (S1) ◽  
pp. S367-S368
Author(s):  
N. Deltort ◽  
J.R. Cazalets ◽  
A. Amestoy ◽  
M. Bouvard
Keyword(s):  
Face Recognition ◽  
Mental Representation ◽  
Recognition Task ◽  
The Self ◽  
Control Group ◽  
Multimodal Integration ◽  
Multisensory Stimulation ◽  
Significant Difference ◽  
Unfamiliar Face ◽  
Multimodal Process

Studies on individuals without developmental disorder show that mental representation of self-face is subject to a multimodal process in the same way that the representation of the self-body is. People with autistic spectrum disorder (ASD) have a particular pattern of face processing and a multimodal integration deficit.The objectives of our study were to evaluate the self-face recognition and the effect of interpersonal multisensory stimulation (IMS) in individuals with ASD. We aimed to show a self-face recognition deficit and a lack of multimodal integration among this population.IMS consisted of the presentation of a movie displaying an unfamiliar face being touched intermittently, while the examiner applied the same stimulation synchronously or asynchronously on the participant. The effect resulting from IMS was measured on two groups with or without ASD by a self-face recognition task on morphing movies made from self-face and unfamiliar-face pictures.There was a significant difference between groups on self-recognition before stimulation. This result shows a self-face recognition deficit in individuals with ASD. Results for the control group showed a significant effect of IMS on self-face recognition in synchronous condition. This suggests the existence of an update of self-face mental representation by multimodal process. In contrast, there was no significant effect of IMS demonstrated in ASD group, suggesting a multimodal integration deficit for the constitution of self-representation in this population.Our results show the existence of a self-face recognition deficit in individuals with ASD, which may be linked to a lack of multimodal integration in the development of the self-face representation.Disclosure of interestThe authors have not supplied their declaration of competing interest.

3D model-based pose invariant face recognition from multiple views

2007 ◽  
Vol 1 (1) ◽  
pp. 25-34 ◽  
Author(s):  
Q. Chen ◽  
J. Yao ◽  
W.K. Cham
Keyword(s):  
Face Recognition ◽  
3D Model ◽  
Multiple Views ◽  
Model Based

scholarly journals Data Augmentation-Assisted Makeup-Invariant Face Recognition

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Muhammad Sajid ◽  
Nouman Ali ◽  
Saadat Hanif Dar ◽  
Naeem Iqbal Ratyal ◽  
Asif Raza Butt ◽  
...  
Keyword(s):  
Face Recognition ◽  
Data Augmentation ◽  
Recognition Performance ◽  
Recognition Task ◽  
Face Images ◽  
Face Features ◽  
Face Datasets ◽  
Exponential Rates ◽  
Interpersonal Situations

Recently, face datasets containing celebrities photos with facial makeup are growing at exponential rates, making their recognition very challenging. Existing face recognition methods rely on feature extraction and reference reranking to improve the performance. However face images with facial makeup carry inherent ambiguity due to artificial colors, shading, contouring, and varying skin tones, making recognition task more difficult. The problem becomes more confound as the makeup alters the bilateral size and symmetry of the certain face components such as eyes and lips affecting the distinctiveness of faces. The ambiguity becomes even worse when different days bring different facial makeup for celebrities owing to the context of interpersonal situations and current societal makeup trends. To cope with these artificial effects, we propose to use a deep convolutional neural network (dCNN) using augmented face dataset to extract discriminative features from face images containing synthetic makeup variations. The augmented dataset containing original face images and those with synthetic make up variations allows dCNN to learn face features in a variety of facial makeup. We also evaluate the role of partial and full makeup in face images to improve the recognition performance. The experimental results on two challenging face datasets show that the proposed approach can compete with the state of the art.

scholarly journals Face Perception Deficits in Developmental Prosopagnosia

2021 ◽  
Author(s):  
◽  
Ella Macaskill
Keyword(s):  
Face Recognition ◽  
Face Perception ◽  
Test Performance ◽  
Large Scale ◽  
Memory Deficits ◽  
Face Memory ◽  
The Face ◽  
Component Processes ◽  
Severe Difficulty ◽  
Scale Experiment

<p>Face recognition is a fundamental cognitive function that is essential for social interaction – yet not everyone has it. Developmental prosopagnosia is a lifelong condition in which people have severe difficulty recognising faces but have normal intellect and no brain damage. Despite much research, the component processes of face recognition that are impaired in developmental prosopagnosia are not well understood. Two core processes are face perception, being the formation of visual representations of a currently seen face, and face memory, being the storage, maintenance, and retrieval of those representations. Most studies of developmental prosopagnosia focus on face memory deficits, but a few recent studies indicate that face perception deficits might also be important. Characterising face perception in developmental prosopagnosia is crucial for a better understanding of the condition. In this thesis, I addressed this issue in a large-scale experiment with 108 developmental prosopagnosics and 136 matched controls. I assessed face perception abilities with multiple measures and ran a broad range of analyses to establish the severity, scope, and nature of face perception deficits in developmental prosopagnosia. Three major results stand out. First, face perception deficits in developmental prosopagnosia were severe, and could be comparable in size to face memory deficits. Second, the face perception deficits were widespread, affecting the whole sample rather than a subset of individuals. Third, the deficits were mainly driven by impairments to mechanisms specialised for processing upright faces. Further analyses revealed several other features of the deficits, including the use of atypical and inconsistent strategies for perceiving faces, difficulties matching the same face across different pictures, equivalent impact of lighting and viewpoint variations in face images, and atypical perceptual and non-perceptual components of test performance. Overall, my thesis shows that face perception deficits are more central to developmental prosopagnosia than previously thought and motivates further research on the issue.</p>

Face Representation Method Using Pixel-to-Vertex Map (PVM) for 3D Model Based Face Recognition

2006 ◽  
pp. 21-28 ◽  
Author(s):  
Taehwa Hong ◽  
Hagbae Kim ◽  
Hyeonjoon Moon ◽  
Yongguk Kim ◽  
Jongweon Lee ◽  
...  
Keyword(s):  
Face Recognition ◽  
3D Model ◽  
Face Representation ◽  
Model Based ◽  
Representation Method ◽  
Vertex Map

Face Recognition Based on Higher Order Neural Network Group-Based Adaptive Tolerance Trees

2021 ◽  
pp. 498-536
Keyword(s):  
Neural Network ◽  
Face Recognition ◽  
Complex Systems ◽  
Face Perception ◽  
Higher Order ◽  
Box Model ◽  
Tree Model ◽  
Translation Invariant ◽  
Network Research ◽  
Simple Models

Recent artificial higher order neural network research has focused on simple models, but such models have not been very successful in describing complex systems (such as face recognition). This chapter presents the artificial higher order neural network group-based adaptive tolerance (HONNGAT) tree model for translation-invariant face recognition. Moreover, face perception classification, detection of front faces with glasses and/or beards models of using HONNGAT trees are presented. The artificial higher order neural network group-based adaptive tolerance tree model is an open box model and can be used to describe complex systems.

scholarly journals Monocular Advantage for Face Perception Implicates Subcortical Mechanisms in Adult Humans

2014 ◽  
Vol 26 (5) ◽  
pp. 927-937 ◽  
Author(s):  
Shai Gabay ◽  
Adrian Nestor ◽  
Eva Dundas ◽  
Marlene Behrmann
Keyword(s):  
Face Recognition ◽  
Face Perception ◽  
Sex Differentiation ◽  
Neural Correlates ◽  
Subcortical Structures ◽  
Adaptive Process ◽  
Cortical Level ◽  
Adult Humans ◽  
Human Adults ◽  
Robust Evidence

The ability to recognize faces accurately and rapidly is an evolutionarily adaptive process. Most studies examining the neural correlates of face perception in adult humans have focused on a distributed cortical network of face-selective regions. There is, however, robust evidence from phylogenetic and ontogenetic studies that implicates subcortical structures, and recently, some investigations in adult humans indicate subcortical correlates of face perception as well. The questions addressed here are whether low-level subcortical mechanisms for face perception (in the absence of changes in expression) are conserved in human adults, and if so, what is the nature of these subcortical representations. In a series of four experiments, we presented pairs of images to the same or different eyes. Participants' performance demonstrated that subcortical mechanisms, indexed by monocular portions of the visual system, play a functional role in face perception. These mechanisms are sensitive to face-like configurations and afford a coarse representation of a face, comprised of primarily low spatial frequency information, which suffices for matching faces but not for more complex aspects of face perception such as sex differentiation. Importantly, these subcortical mechanisms are not implicated in the perception of other visual stimuli, such as cars or letter strings. These findings suggest a conservation of phylogenetically and ontogenetically lower-order systems in adult human face perception. The involvement of subcortical structures in face recognition provokes a reconsideration of current theories of face perception, which are reliant on cortical level processing, inasmuch as it bolsters the cross-species continuity of the biological system for face recognition.

Sign in / Sign up

Export Citation Format

Share Document