Face Recognition in the Dark: A Unified Approach for NIR- VIS and VIS- NIR Face Matching

2020 ◽  
Author(s):  
Nilu R. Salim ◽  
Umarani Jayaraman ◽  
V Srinath
Keyword(s):  
Face Recognition ◽  
Unified Approach ◽  
Face Matching

scholarly journals Enhanced Matching of Children’s Faces in “Super-Recognisers” But Not High-Contact Controls

i-Perception ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 204166952094442
Author(s):  
Sarah Bate ◽  
Rachel Bennetts ◽  
Ebony Murray ◽  
Emma Portch
Keyword(s):  
Face Recognition ◽  
Young Children ◽  
Real World ◽  
Matching Task ◽  
Control Groups ◽  
Age Bias ◽  
Face Matching ◽  
Contact Control ◽  
Additional Exposure

Face matching is notoriously error-prone, and some work suggests additional difficulty when matching the faces of children. It is possible that individuals with natural proficiencies in adult face matching (“super-recognisers” [SRs]) will also excel at the matching of children’s faces, although other work implicates facilitations in typical perceivers who have high levels of contact with young children (e.g., nursery teachers). This study compared the performance of both of these groups on adult and child face matching to a group of low-contact controls. High- and low-contact control groups performed at a remarkably similar level in both tasks, whereas facilitations for adult and child face matching were observed in some (but not all) SRs. As a group, the SRs performed better in the adult compared with the child task, demonstrating an extended own-age bias compared with controls. These findings suggest that additional exposure to children’s faces does not assist the performance in a face matching task, and the mechanisms underpinning superior recognition of adult faces can also facilitate the child face recognition. Real-world security organisations should therefore seek individuals with general facilitations in face matching for both adult and child face matching tasks.

scholarly journals Comparative analysis of selected facial recognition algorithms

2020 ◽  
Vol 39 (3) ◽  
pp. 896-904
Author(s):  
J.A. Popoola ◽  
C.O. Yinka-Banjo
Keyword(s):  
Face Recognition ◽  
Comparative Analysis ◽  
Facial Recognition ◽  
Research Work ◽  
Cost Effective ◽  
Facial Symmetry ◽  
Face Matching ◽  
Computer Based ◽  
Haar Cascade ◽  
Detection And Recognition

Systems and applications embedded with facial detection and recognition capabilities are founded on the notion that there are differences in face structures among individuals, and as such, we can perform face-matching using the facial symmetry. A widely used application of facial detection and recognition is in security. It is important that the images be processed correctly for computer-based facial recognition, hence, the usage of efficient, cost-effective algorithms and a robust database. This research work puts these measures into consideration and attempts to determine a cost-effective and reliable algorithm out of three algorithms examined. Keywords: Haar-Cascade, PCA, Eigenfaces, Fisherfaces, LBPH, Face Recognition.

scholarly journals Surgical face masks impair human face matching performance for familiar and unfamiliar faces

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Daniel J. Carragher ◽  
Peter J. B. Hancock
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Human Face ◽  
Face Matching ◽  
Face Recognition System ◽  
Surgical Masks ◽  
The Face ◽  
Matching Performance ◽  
Recognition Systems ◽  
Unfamiliar Faces

AbstractIn response to the COVID-19 pandemic, many governments around the world now recommend, or require, that their citizens cover the lower half of their face in public. Consequently, many people now wear surgical face masks in public. We investigated whether surgical face masks affected the performance of human observers, and a state-of-the-art face recognition system, on tasks of perceptual face matching. Participants judged whether two simultaneously presented face photographs showed the same person or two different people. We superimposed images of surgical masks over the faces, creating three different mask conditions: control (no masks), mixed (one face wearing a mask), and masked (both faces wearing masks). We found that surgical face masks have a large detrimental effect on human face matching performance, and that the degree of impairment is the same regardless of whether one or both faces in each pair are masked. Surprisingly, this impairment is similar in size for both familiar and unfamiliar faces. When matching masked faces, human observers are biased to reject unfamiliar faces as “mismatches” and to accept familiar faces as “matches”. Finally, the face recognition system showed very high classification accuracy for control and masked stimuli, even though it had not been trained to recognise masked faces. However, accuracy fell markedly when one face was masked and the other was not. Our findings demonstrate that surgical face masks impair the ability of humans, and naïve face recognition systems, to perform perceptual face matching tasks. Identification decisions for masked faces should be treated with caution.

scholarly journals Boosting Face Recognition under Drastic Views Using a Pose AutoAugment Manner

2020 ◽  
Vol 10 (24) ◽  
pp. 8940
Author(s):  
Wanshun Gao ◽  
Xi Zhao ◽  
Jianhua Zou
Keyword(s):  
Neural Network ◽  
Face Recognition ◽  
The Third ◽  
Correlation Score ◽  
Face Matching ◽  
Invariant Feature ◽  
The Face ◽  
3D Databases ◽  
Model Training ◽  
Facial Images

Face recognition under drastic pose drops rapidly due to the limited samples during the model training. In this paper, we propose a pose-autoaugment face recognition framework (PAFR) based on the training of a Convolutional Neural Network (CNN) with multi-view face augmentation. The proposed framework consists of three parts: face augmentation, CNN training, and face matching. The face augmentation part is composed of pose autoaugment and background appending for increasing the pose variations of each subject. In the second part, we train a CNN model with the generated facial images to enhance the pose-invariant feature extraction. In the third part, we concatenate the feature vectors of each face and its horizontally flipped face from the trained CNN model to obtain a robust feature. The correlation score between the two faces is computed by the cosine similarity of their robust features. Comparable experiments are demonstrated on Bosphorus and CASIA-3D databases.

scholarly journals Individual differences in emotion regulation and face recognition

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243209
Author(s):  
Ahmed M. Megreya ◽  
Robert D. Latzman
Keyword(s):  
Emotion Regulation ◽  
Face Recognition ◽  
Individual Differences ◽  
Cognitive Reappraisal ◽  
False Positives ◽  
Emotion Regulation Strategies ◽  
Expressive Suppression ◽  
Face Memory ◽  
Face Matching ◽  
Regulation Strategies

Face recognition ability is highly variable among neurologically intact populations. Across three experiments, this study examined for the first time associations between individual differences in a range of adaptive versus maladaptive emotion regulation strategies and face recognition. Using an immediate face-memory paradigm, in which observers had to identify a self-paced learned unfamiliar face from a 10-face target-present/ target-absent line-up, Experiment 1 (N = 42) found high levels of expressive suppression (the ongoing efforts to inhibit emotion-expressive behaviors), but not cognitive reappraisal (the cognitive re-evaluation of emotional events to change their emotional consequences), were associated with a lower level of overall face-memory accuracy and higher rates of misidentifications and false positives. Experiment 2 (N = 53) replicated these finding using a range of face-matching tasks, where observers were asked to match pairs of same-race or different-race face images taken on the same day or during different times. Once again, high levels of expressive suppression were associated with a lower level of overall face-matching performance and higher rates of false positives, but cognitive reappraisal did not correlate with any face-matching measure. Finally, Experiment 3 (N = 52) revealed that the higher use of maladaptive cognitive emotion regulation strategies, especially catastrophizing, was associated with lower levels of overall face-matching performances and higher rates of false positives. All told, the current research provides new evidence concerning the important associations between emotion and cognition.

scholarly journals The Goldsmiths Unfamiliar Face Memory and Before They Were Adult Tests

2020 ◽  
Author(s):  
Ashok Jansari ◽  
E. Green ◽  
Francesco Innocenti ◽  
Diego Nardi ◽  
Elena Belanova ◽  
...  
Keyword(s):  
Face Recognition ◽  
Holistic Processing ◽  
Face Identification ◽  
Facial Features ◽  
Face Memory ◽  
Face Matching ◽  
Recognition Ability ◽  
Unfamiliar Face ◽  
The Continuum

Unfamiliar face identification ability varies widely in the population. Those at the extreme top and bottom ends of the continuum have been labelled super-recognisers and prosopagnosics, respectively. Here we describe the development of two new tests - the Goldsmiths Unfamiliar Face Memory Test (GUFMT) and the Before They Were Adult Test (BTWA), that have been designed to measure different aspects of face identity ability across the spectrum. The GUFMT is a test of face memory, the BTWA a test of simultaneous adult-to-child face matching. Their designs draw on theories suggesting face identification is achieved by the recognition of facial features, the consistency across time of configurations between those features, and holistic processing of faces as a Gestalt. In four phases, participants (n = 16737), recruited using different methods, allowed evaluations to drive GUFMT development, the creation of likely population norms, as well as correlations with established face recognition tests. Recommendations for criteria for classification of super-recognition ability are also made.

scholarly journals EXPRESS: When Two Fields Collide: Identifying “Super-Recognisers” for Neuropsychological and Forensic Face Recognition Research

2021 ◽  
pp. 174702182110276
Author(s):  
Sarah Bate ◽  
Emma Portch ◽  
Natalie Mestry
Keyword(s):  
Face Recognition ◽  
Individual Differences ◽  
Facial Identity ◽  
Common Definition ◽  
Face Matching ◽  
Recognition Ability ◽  
The Face ◽  
The One ◽  
Definition Of ◽  
Matching Field

In the last decade, a novel individual differences approach has emerged across the face recognition literature. While the field has long been concerned with prosopagnosia (the inability to recognise facial identity), it has more recently become clear that there are vast differences in face recognition ability within the typical population. “Super-recognisers” are those individuals purported to reside at the very top of this spectrum. On the one hand, these people are of interest to cognitive neuropsychologists who are motivated to explore the commonality of the face recognition continuum, whereas researchers from the forensic face matching field evaluate the implementation of super-recognisers into real-world police and security settings. These two rather different approaches have led to discrepancies in the definition of super-recognisers, and perhaps more fundamentally, the approach to identifying them, resulting in a lack of consistency that prohibits theoretical progress. Here, we review the protocols used in published work to identify super-recognisers, and propose a common definition and screening recommendations that can be adhered to across fields.

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