Effects of Uniqueness, Sex of Subject, and Sex of Photograph on Facial Recognition

1974 ◽  
Vol 39 (1) ◽  
pp. 109-110 ◽  
Author(s):  
Merideth Going ◽  
J. D. Read
Keyword(s):  
Face Recognition ◽  
Facial Recognition ◽  
Recognition Task ◽  
Male And Female

In a face-recognition task, highly unique faces were correctly identified more often than low-unique faces and female faces more frequently than male faces. At both levels of uniqueness, female Ss recognized female faces more frequently than male faces whereas male Ss recognized male and female faces with equal facility.

Perceptual Effects and Recollective Experience in Face Recognition

2005 ◽  
Vol 52 (3) ◽  
pp. 224-231 ◽  
Author(s):  
Chrisanthi Nega
Keyword(s):  
Face Recognition ◽  
Recognition Memory ◽  
Congruency Effect ◽  
Facial Recognition ◽  
Memory Systems ◽  
Study Time ◽  
Perceptual Fluency ◽  
Recollective Experience ◽  
Trace Strength ◽  
Size Congruency

Abstract. Four experiments were conducted investigating the effect of size congruency on facial recognition memory, measured by remember, know and guess responses. Different study times were employed, that is extremely short (300 and 700 ms), short (1,000 ms), and long times (5,000 ms). With the short study time (1,000 ms) size congruency occurred in knowing. With the long study time the effect of size congruency occurred in remembering. These results support the distinctiveness/fluency account of remembering and knowing as well as the memory systems account, since the size congruency effect that occurred in knowing under conditions that facilitated perceptual fluency also occurred independently in remembering under conditions that facilitated elaborative encoding. They do not support the idea that remember and know responses reflect differences in trace strength.

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.

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 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.

scholarly journals Social Factors Influence Behavior in the Novel Object Recognition Task in a Mouse Model of Down Syndrome

2021 ◽  
Vol 15 ◽  
Author(s):  
Cesar Sierra ◽  
Ilario De Toma ◽  
Lorenzo Lo Cascio ◽  
Esteban Vegas ◽  
Mara Dierssen
Keyword(s):  
Down Syndrome ◽  
Object Recognition ◽  
Environmental Factors ◽  
Mouse Models ◽  
Recognition Task ◽  
Novel Object Recognition ◽  
The Novel ◽  
Wild Type ◽  
Male And Female ◽  
Novel Object

The use of mouse models has revolutionized the field of Down syndrome (DS), increasing our knowledge about neuropathology and helping to propose new therapies for cognitive impairment. However, concerns about the reproducibility of results in mice and their translatability to humans have become a major issue, and controlling for moderators of behavior is essential. Social and environmental factors, the experience of the researcher, and the sex and strain of the animals can all have effects on behavior, and their impact on DS mouse models has not been explored. Here we analyzed the influence of a number of social and environmental factors, usually not taken into consideration, on the behavior of male and female wild-type and trisomic mice (the Ts65Dn model) in one of the most used tests for proving drug effects on memory, the novel object recognition (NOR) test. Using principal component analysis and correlation matrices, we show that the ratio of trisomic mice in the cage, the experience of the experimenter, and the timing of the test have a differential impact on male and female and on wild-type and trisomic behavior. We conclude that although the NOR test is quite robust and less susceptible to environmental influences than expected, to obtain useful results, the phenotype expression must be contrasted against the influences of social and environmental factors.

scholarly journals InnovFaceNet: Deep Face Recognition for Industrial Environments

2021 ◽  
Vol 6 (1) ◽  
pp. 1-4
Author(s):  
Nagarjun Gururaj ◽  
Kanika Batra
Keyword(s):  
Face Recognition ◽  
Criminal Justice ◽  
Real Time ◽  
Intelligent Systems ◽  
Facial Recognition ◽  
Industrial Plant ◽  
The World ◽  
Industrial Environments ◽  
Or Organization ◽  
Security Surveillance

In recent times the usage of intelligent systems have paved way formany applications to be robust and self-reliant. One such popularand vast growing technology is face recognition. Facial Recognitiontechnology is used in security, surveillance, criminal justice systemsand many other multimedia platforms. This work proposes a realtime facial recognition technology which can be used in any industrialsetup eliminating manual supervision, ensuring authorized accessto the personnel in the plant. Due to the recent development ofCOVID-19 pandemic around the world, wearing masks has becomea necessity. Our proposed facial recognition technology identifies aperson’s face with mask or no mask in real time with a speed of20 FPS on a CPU and an F1-score of 95.07%. This makes ouralgorithm fast, secure, robust and deployable on a simple personalcomputer or any edge device at any industrial plant or organization.

scholarly journals Alcohol myopia and the distracting effects of hair in face recognition

2019 ◽  
Vol 34 (2) ◽  
pp. 237-244
Author(s):  
Alistair J Harvey ◽  
Danny A Tomlinson
Keyword(s):  
Facial Recognition ◽  
Recognition Task ◽  
Cognitive Resources ◽  
Exterior Region ◽  
Eyewitness Accuracy ◽  
Alcohol Myopia ◽  
Unfamiliar Face ◽  
Alcohol Myopia Theory ◽  
Full Face ◽  
Unfamiliar Faces

Background: According to alcohol myopia theory, alcohol reduces cognitive resources and restricts the drinker’s attention to only the more prominent aspects of a visual scene. As human hairstyles are often salient and serve as important facial recognition cues, we consider whether alcohol restricts attention to this region of faces upon initial viewing. Aims: Participants with higher breath alcohol concentrations just prior to encoding a series of unfamiliar faces were expected to be poorer than more sober counterparts at recognising the internal but not external features of those faces at test. Methods: Drinkers in a nearby bar ( n=76) were breathalysed and then shown a sequence of 21 full face photos. After a filled five-minute retention interval they completed a facial recognition task requiring them to identify the full, internal or external region of each of these among a sequence of 21 previously unseen (part or whole) faces. Results: As predicted, higher breath concentrations were associated with poorer discrimination of internal but not external face regions. Conclusions: Our findings suggest that alcohol restricts unfamiliar face encoding by narrowing the scope of attention to the exterior region of unfamiliar faces. This has important implications for drunk eyewitness accuracy, though further investigation is needed to see if the effect is mediated by gender, hair length and face feature distinctiveness.

Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor

2017 ◽  
Vol 7 (3) ◽  
pp. 1594 ◽  
Author(s):  
Taha H. Rassem ◽  
Nasrin M. Makbol ◽  
Sam Yin Yee
Keyword(s):  
Face Recognition ◽  
Recognition Task ◽  
Texture Features ◽  
Classification Rate ◽  
Local Ternary Pattern ◽  
Japanese Female ◽  
The Face ◽  
Recognition Systems ◽  
High Recognition Accuracy ◽  
Event Image

Nowadays, face recognition becomes one of the important topics in the computer vision and image processing area. This is due to its importance where can be used in many applications. The main key in the face recognition is how to extract distinguishable features from the image to perform high recognition accuracy.  Local binary pattern (LBP) and many of its variants used as texture features in many of face recognition systems. Although LBP performed well in many fields, it is sensitive to noise, and different patterns of LBP may classify into the same class that reduces its discriminating property. Completed Local Ternary Pattern (CLTP) is one of the new proposed texture features to overcome the drawbacks of the LBP. The CLTP outperformed LBP and some of its variants in many fields such as texture, scene, and event image classification.  In this study, we study and investigate the performance of CLTP operator for face recognition task. The Japanese Female Facial Expression (JAFFE), and FEI face databases are used in the experiments. In the experimental results, CLTP outperformed some previous texture descriptors and achieves higher classification rate for face recognition task which has reached up 99.38% and 85.22% in JAFFE and FEI, respectively.

scholarly journals A Web-Based Mobile Attendance System with Facial Recognition Feature

2020 ◽  
Vol 14 (05) ◽  
pp. 193
Author(s):  
Noradila Nordin ◽  
Nurul Husna Mohd Fauzi
Keyword(s):  
Face Recognition ◽  
Mobile Devices ◽  
Conventional Method ◽  
Facial Recognition ◽  
Recognition System ◽  
Web Based ◽  
Face Recognition System ◽  
The Face ◽  
System Prototype

Attendance marking in a classroom is one of the methods used to track the student’s presence in the lecture. The conventional method that is being enforced has shown to be vulnerable, inaccurate and time-consuming especially in a large classroom. It is difficult to identify absentees and proxy attendees based on the conventional attendance marking method. In order to overcome the challenges faced in the conventional method, a web-based mobile attendance system with facial recognition feature is proposed. It incorporated the existing mobile devices with a camera and the face recognition system to allow the attendance system to be used in classrooms automatically and efficiently with minor implementation requirements. The system prototype received positive responses from the volunteers who tested the system to replace the conventional attendance marking.

Sign in / Sign up

Export Citation Format

Share Document