Search Results for author:
Found 66 papers, 26 papers with code
Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data
Synthetic data is gaining increasing relevance for training machine learning models.
Is my Data in your AI Model? Membership Inference Test with Application to Face Images
This paper introduces the Membership Inference Test (MINT), a novel approach that aims to empirically assess if specific data was used during the training of Artificial Intelligence (AI) models.
Synthetic Data for the Mitigation of Demographic Biases in Face Recognition
They primarily arise from the unequal representations of demographic groups in the training data.
IEEE BigData 2023 Keystroke Verification Challenge (KVC)
Several neural architectures were proposed by the participants, leading to global Equal Error Rates (EERs) as low as 3. 33% and 3. 61% achieved by the best team respectively in the desktop and mobile scenario, outperforming the current state of the art biometric verification performance for KD.
How Good is ChatGPT at Face Biometrics? A First Look into Recognition, Soft Biometrics, and Explainability
In particular, we analyze the ability of ChatGPT to perform tasks such as face verification, soft-biometrics estimation, and explainability of the results.
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must be covered in more detail.
Keystroke Verification Challenge (KVC): Biometric and Fairness Benchmark Evaluation
Analyzing keystroke dynamics (KD) for biometric verification has several advantages: it is among the most discriminative behavioral traits; keyboards are among the most common human-computer interfaces, being the primary means for users to enter textual data; its acquisition does not require additional hardware, and its processing is relatively lightweight; and it allows for transparently recognizing subjects.
SaFL: Sybil-aware Federated Learning with Application to Face Recognition
Federated Learning (FL) is a machine learning paradigm to conduct collaborative learning among clients on a joint model.
PAD-Phys: Exploiting Physiology for Presentation Attack Detection in Face Biometrics
Presentation Attack Detection (PAD) is a crucial stage in facial recognition systems to avoid leakage of personal information or spoofing of identity to entities.
mEBAL2 Database and Benchmark: Image-based Multispectral Eyeblink Detection
This work introduces a new multispectral database and novel approaches for eyeblink detection in RGB and Near-Infrared (NIR) individual images.
AI4Food-NutritionFW: A Novel Framework for the Automatic Synthesis and Analysis of Eating Behaviours
In addition to the framework, we also provide and describe a unique food image dataset that includes 4, 800 different weekly eating behaviours from 15 different profiles and 1, 200 subjects.
Document Layout Annotation: Database and Benchmark in the Domain of Public Affairs
Every day, thousands of digital documents are generated with useful information for companies, public organizations, and citizens.
Leveraging Large Language Models for Topic Classification in the Domain of Public Affairs
The analysis of public affairs documents is crucial for citizens as it promotes transparency, accountability, and informed decision-making.
M2LADS: A System for Generating MultiModal Learning Analytics Dashboards in Open Education
In this article, we present a Web-based System called M2LADS, which supports the integration and visualization of multimodal data recorded in learning sessions in a MOOC in the form of Web-based Dashboards.
Measuring Bias in AI Models: An Statistical Approach Introducing N-Sigma
This risk assessment should address, among others, the detection and mitigation of bias in AI.
OTB-morph: One-Time Biometrics via Morphing
Cancelable biometrics are a group of techniques to transform the input biometric to an irreversible feature intentionally using a transformation function and usually a key in order to provide security and privacy in biometric recognition systems.
Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitment
With the aim of studying how current multimodal algorithms based on heterogeneous sources of information are affected by sensitive elements and inner biases in the data, we propose a fictitious case study focused on automated recruitment: FairCVtest.
Toward Face Biometric De-identification using Adversarial Examples
The remarkable success of face recognition (FR) has endangered the privacy of internet users particularly in social media.
MATT: Multimodal Attention Level Estimation for e-learning Platforms
This work presents a new multimodal system for remote attention level estimation based on multimodal face analysis.
TypeFormer: Transformers for Mobile Keystroke Biometrics
The broad usage of mobile devices nowadays, the sensitiveness of the information contained in them, and the shortcomings of current mobile user authentication methods are calling for novel, secure, and unobtrusive solutions to verify the users' identity.
edBB-Demo: Biometrics and Behavior Analysis for Online Educational Platforms
We present edBB-Demo, a demonstrator of an AI-powered research platform for student monitoring in remote education.
Leveraging Automatic Personalised Nutrition: Food Image Recognition Benchmark and Dataset based on Nutrition Taxonomy
Maintaining a healthy lifestyle has become increasingly challenging in today's sedentary society marked by poor eating habits.
IJCB 2022 Mobile Behavioral Biometrics Competition (MobileB2C)
This paper describes the experimental framework and results of the IJCB 2022 Mobile Behavioral Biometrics Competition (MobileB2C).
BeCAPTCHA-Type: Biometric Keystroke Data Generation for Improved Bot Detection
Different bot detectors are considered based on several supervised classifiers (Support Vector Machine, Random Forest, Gaussian Naive Bayes and a Long Short-Term Memory network) and a learning framework including human and synthetic samples.
Mobile Keystroke Biometrics Using Transformers
One of the most popular traits in the literature is keystroke dynamics due to the large deployment of computers and mobile devices in our society.
BehavePassDB: Public Database for Mobile Behavioral Biometrics and Benchmark Evaluation
Mobile behavioral biometrics have become a popular topic of research, reaching promising results in terms of authentication, exploiting a multimodal combination of touchscreen and background sensor data.
Mobile Behavioral Biometrics for Passive Authentication
Current mobile user authentication systems based on PIN codes, fingerprint, and face recognition have several shortcomings.
FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment
This comparison shows that, even though FaceQgen does not surpass the best existing face quality assessment methods in terms of face recognition accuracy prediction, it achieves good enough results to demonstrate the potential of semi-supervised learning approaches for quality estimation (in particular, data-driven learning based on a single high quality image per subject), having the capacity to improve its performance in the future with adequate refinement of the model and the significant advantage over competing methods of not needing quality labels for its development.
ALEBk: Feasibility Study of Attention Level Estimation via Blink Detection applied to e-Learning
The experimental framework is carried out using a public multimodal database for eye blink detection and attention level estimation called mEBAL, which comprises data from 38 students and multiples acquisition sensors, in particular, i) an electroencephalogram (EEG) band which provides the time signals coming from the student's cognitive information, and ii) RGB and NIR cameras to capture the students face gestures.
OTB-morph: One-Time Biometrics via Morphing applied to Face Templates
Cancelable biometrics refers to a group of techniques in which the biometric inputs are transformed intentionally using a key before processing or storage.
Introduction to Presentation Attack Detection in Iris Biometrics and Recent Advances
Iris recognition technology has attracted an increasing interest in the last decades in which we have witnessed a migration from research laboratories to real world applications.
Introduction to Presentation Attack Detection in Face Biometrics and Recent Advances
The main scope of this chapter is to serve as an introduction to face presentation attack detection, including key resources and advances in the field in the last few years.
FaceQvec: Vector Quality Assessment for Face Biometrics based on ISO Compliance
In this paper we develop FaceQvec, a software component for estimating the conformity of facial images with each of the points contemplated in the ISO/IEC 19794-5, a quality standard that defines general quality guidelines for face images that would make them acceptable or unacceptable for use in official documents such as passports or ID cards.
GaitPrivacyON: Privacy-Preserving Mobile Gait Biometrics using Unsupervised Learning
This study proposes GaitPrivacyON, a novel mobile gait biometrics verification approach that provides accurate authentication results while preserving the sensitive information of the subject.
IFBiD: Inference-Free Bias Detection
This paper is the first to explore an automatic way to detect bias in deep convolutional neural networks by simply looking at their weights.
SetMargin Loss applied to Deep Keystroke Biometrics with Circle Packing Interpretation
This work presents a new deep learning approach for keystroke biometrics based on a novel Distance Metric Learning method (DML).
SVC-onGoing: Signature Verification Competition
This article presents SVC-onGoing, an on-going competition for on-line signature verification where researchers can easily benchmark their systems against the state of the art in an open common platform using large-scale public databases, such as DeepSignDB and SVC2021_EvalDB, and standard experimental protocols.
SELM: Siamese Extreme Learning Machine with Application to Face Biometrics
For these reasons, we propose and develop a Siamese Extreme Learning Machine (SELM).
ICDAR 2021 Competition on On-Line Signature Verification
This paper describes the experimental framework and results of the ICDAR 2021 Competition on On-Line Signature Verification (SVC 2021).
A Comprehensive Study on Face Recognition Biases Beyond Demographics
However, to enable a trustworthy FR technology, it is essential to know the influence of an extended range of facial attributes on FR beyond demographics.
Child-Computer Interaction with Mobile Devices: Recent Works, New Dataset, and Age Detection
This article provides an overview of recent research in Child-Computer Interaction with mobile devices and describe our framework ChildCI intended for: i) overcoming the lack of large-scale publicly available databases in the area, ii) generating a better understanding of the cognitive and neuromotor development of children along time, contrary to most previous studies in the literature focused on a single-session acquisition, and iii) enabling new applications in e-Learning and e-Health through the acquisition of additional information such as the school grades and children's disorders, among others.
TypeNet: Deep Learning Keystroke Biometrics
We study the performance of Long Short-Term Memory networks for keystroke biometric authentication at large scale in free-text scenarios.
Exploring Facial Expressions and Affective Domains for Parkinson Detection
The principal contributions of this work are: (1) a novel framework to exploit deep face architectures to model hypomimia in PD patients; (2) we experimentally compare PD detection based on single images vs. image sequences while the patients are evoked various face expressions; (3) we explore different domain adaptation techniques to exploit existing models initially trained either for Face Recognition or to detect FAUs for the automatic discrimination between PD patients and healthy subjects; and (4) a new approach to use triplet-loss learning to improve hypomimia modeling and PD detection.
Symbolic AI for XAI: Evaluating LFIT Inductive Programming for Fair and Explainable Automatic Recruitment
Machine learning methods are growing in relevance for biometrics and personal information processing in domains such as forensics, e-health, recruitment, and e-learning.
BIG-bench Machine Learning
Explainable Artificial Intelligence (XAI)
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Facial Expressions as a Vulnerability in Face Recognition
This work explores facial expression bias as a security vulnerability of face recognition systems.
DeepFakesON-Phys: DeepFakes Detection based on Heart Rate Estimation
This work introduces a novel DeepFake detection framework based on physiological measurement.
Learning Emotional-Blinded Face Representations
We propose two face representations that are blind to facial expressions associated to emotional responses.
DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representations
These two properties give a lot of flexibility to our synthesiser, e. g., as shown in our experiments, DeepWriteSYN can generate realistic handwriting variations of a given handwritten structure corresponding to the natural variation within a given population or a given subject.
FairCVtest Demo: Understanding Bias in Multimodal Learning with a Testbed in Fair Automatic Recruitment
With the aim of studying how current multimodal AI algorithms based on heterogeneous sources of information are affected by sensitive elements and inner biases in the data, this demonstrator experiments over an automated recruitment testbed based on Curriculum Vitae: FairCVtest.
mEBAL: A Multimodal Database for Eye Blink Detection and Attention Level Estimation
This work presents mEBAL, a multimodal database for eye blink detection and attention level estimation.
Heart Rate Estimation from Face Videos for Student Assessment: Experiments on edBB
In this study we estimate the heart rate from face videos for student assessment.
A Comparative Evaluation of Heart Rate Estimation Methods using Face Videos
This paper presents a comparative evaluation of methods for remote heart rate estimation using face videos, i. e., given a video sequence of the face as input, methods to process it to obtain a robust estimation of the subjects heart rate at each moment.
Keystroke Biometrics in Response to Fake News Propagation in a Global Pandemic
Behavioral biometrics can be powerful tools in this fight.
BeCAPTCHA-Mouse: Synthetic Mouse Trajectories and Improved Bot Detection
We propose two new mouse trajectory synthesis methods for generating realistic data: a) a function-based method based on heuristic functions, and b) a data-driven method based on Generative Adversarial Networks (GANs) in which a Generator synthesizes human-like trajectories from a Gaussian noise input.
SensitiveLoss: Improving Accuracy and Fairness of Face Representations with Discrimination-Aware Deep Learning
We propose a discrimination-aware learning method to improve both accuracy and fairness of biased face recognition algorithms.
Bias in Multimodal AI: Testbed for Fair Automatic Recruitment
With the aim of studying how current multimodal algorithms based on heterogeneous sources of information are affected by sensitive elements and inner biases in the data, we propose a fictitious automated recruitment testbed: FairCVtest.
InsideBias: Measuring Bias in Deep Networks and Application to Face Gender Biometrics
We analyze how bias affects deep learning processes through a toy example using the MNIST database and a case study in gender detection from face images.
Blockchain in the Internet of Things: Architectures and Implementation
The world is becoming more interconnected every day.
Cryptography and Security Computers and Society
TypeNet: Scaling up Keystroke Biometrics
We study the suitability of keystroke dynamics to authenticate 100K users typing free-text.
DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection
The free access to large-scale public databases, together with the fast progress of deep learning techniques, in particular Generative Adversarial Networks, have led to the generation of very realistic fake content with its corresponding implications towards society in this era of fake news.
edBB: Biometrics and Behavior for Assessing Remote Education
We present a platform for student monitoring in remote education consisting of a collection of sensors and software that capture biometric and behavioral data.
Algorithmic Discrimination: Formulation and Exploration in Deep Learning-based Face Biometrics
We experimentally show that demographic groups highly represented in popular face databases have led to popular pre-trained deep face models presenting strong algorithmic discrimination.
FaceGenderID: Exploiting Gender Information in DCNNs Face Recognition Systems
We observe a gap between face verification performances obtained by both gender classes.
Quality-based Pulse Estimation from NIR Face Video with Application to Driver Monitoring
In this paper we develop a robust for heart rate (HR) estimation method using face video for challenging scenarios with high variability sources such as head movement, illumination changes, vibration, blur, etc.
SensitiveNets: Learning Agnostic Representations with Application to Face Images
Our method is based on an adversarial regularizer that introduces a sensitive information removal function in the learning objective.
MultiLock: Mobile Active Authentication based on Multiple Biometric and Behavioral Patterns
In this paper we evaluate mobile active authentication based on an ensemble of biometrics and behavior-based profiling signals.
