Search Results for author:
Found 97 papers, 32 papers with code
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.
FaceQnet: Quality Assessment for Face Recognition based on Deep Learning
Several conclusions can be drawn from this work, most notably: 1) we managed to employ an existing ICAO compliance framework and a pretrained CNN to automatically label data with quality information, 2) we trained FaceQnet for quality estimation by fine-tuning a pre-trained face recognition network (ResNet-50), and 3) we have shown that the predictions from FaceQnet are highly correlated with the face recognition accuracy of a state-of-the-art commercial system not used during development.
Biometric Quality: Review and Application to Face Recognition with FaceQnet
After a gentle introduction to the general topic of biometric quality and a review of past efforts in face quality metrics, in the present work, we address the need for better face quality metrics by developing FaceQnet.
DeepFakesON-Phys: DeepFakes Detection based on Heart Rate Estimation
This work introduces a novel DeepFake detection framework based on physiological measurement.
DeepSign: Deep On-Line Signature Verification
Deep learning has become a breathtaking technology in the last years, overcoming traditional handcrafted approaches and even humans for many different tasks.
GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detection
The availability of large-scale facial databases, together with the remarkable progresses of deep learning technologies, in particular Generative Adversarial Networks (GANs), have led to the generation of extremely realistic fake facial content, raising obvious concerns about the potential for misuse.
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.
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.
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.
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.
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.
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.
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.
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.
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.
SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data
This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 International Joint Conference on Biometrics (IJCB 2023).
Are Adaptive Face Recognition Systems still Necessary? Experiments on the APE Dataset
In the last five years, deep learning methods, in particular CNN, have attracted considerable attention in the field of face-based recognition, achieving impressive results.
IJCB 2022 Mobile Behavioral Biometrics Competition (MobileB2C)
This paper describes the experimental framework and results of the IJCB 2022 Mobile Behavioral Biometrics Competition (MobileB2C).
Blockchain meets Biometrics: Concepts, Application to Template Protection, and Trends
Blockchain technologies provide excellent architectures and practical tools for securing and managing the sensitive and private data stored in biometric templates, but at a cost.
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.
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).
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.
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.
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.
BioTouchPass2: Touchscreen Password Biometrics Using Time-Aligned Recurrent Neural Networks
ii) We perform a complete analysis of the proposed approach considering both traditional authentication systems such as Dynamic Time Warping (DTW) and novel approaches based on Recurrent Neural Networks (RNNs).
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.
BioTouchPass: Handwritten Passwords for Touchscreen Biometrics
A complete analysis of our proposed biometric system is carried out regarding the discriminative power of each handwritten digit and the robustness when increasing the length of the password and the number of enrolment samples.
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.
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.
Improving Automated Latent Fingerprint Identification using Extended Minutia Types
We report significant improvements in the rank identification accuracies when these minutiae matchers are augmented with our proposed algorithm based on rare minutiae features.
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.
Cross-Sensor Periocular Biometrics in a Global Pandemic: Comparative Benchmark and Novel Multialgorithmic Approach
Experiments are also reported with a database of VIS images from different smartphones.
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.
Biometric Template Storage with Blockchain: A First Look into Cost and Performance Tradeoffs
We explore practical tradeoffs in blockchain-based biometric template storage.
Cryptography and Security
TypeNet: Scaling up Keystroke Biometrics
We study the suitability of keystroke dynamics to authenticate 100K users typing free-text.
Blockchain in the Internet of Things: Architectures and Implementation
The world is becoming more interconnected every day.
Cryptography and Security Computers and Society
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.
DeepFakes Evolution: Analysis of Facial Regions and Fake Detection Performance
Media forensics has attracted a lot of attention in the last years in part due to the increasing concerns around DeepFakes.
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.
Keystroke Biometrics in Response to Fake News Propagation in a Global Pandemic
Behavioral biometrics can be powerful tools in this fight.
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.
Quickest Intruder Detection for Multiple User Active Authentication
In this paper, we investigate how to detect intruders with low latency for Active Authentication (AA) systems with multiple-users.
Face Image Quality Assessment: A Literature Survey
The performance of face analysis and recognition systems depends on the quality of the acquired face data, which is influenced by numerous factors.
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.
Learning Emotional-Blinded Face Representations
We propose two face representations that are blind to facial expressions associated to emotional responses.
Facial Expressions as a Vulnerability in Face Recognition
This work explores facial expression bias as a security vulnerability of face recognition systems.
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)
+1
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.
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.
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.
SELM: Siamese Extreme Learning Machine with Application to Face Biometrics
For these reasons, we propose and develop a Siamese Extreme Learning Machine (SELM).
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).
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.
Direct attacks using fake images in iris verification
In this contribution, the vulnerabilities of iris-based recognition systems to direct attacks are studied.
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.
A high performance fingerprint liveness detection method based on quality related features
A new software-based liveness detection approach using a novel fingerprint parameterization based on quality related features is proposed.
BiosecurID: a multimodal biometric database
A new multimodal biometric database, acquired in the framework of the BiosecurID project, is presented together with the description of the acquisition setup and protocol.
A Comparative Study of Fingerprint Image-Quality Estimation Methods
One of the open issues in fingerprint verification is the lack of robustness against image-quality degradation.
The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)
It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware.
Benchmarking Quality-Dependent and Cost-Sensitive Score-Level Multimodal Biometric Fusion Algorithms
The cost-sensitive evaluation, on the other hand, investigates how well a fusion algorithm can perform given restricted computation and in the presence of software and hardware failures, resulting in errors such as failure-to-acquire and failure-to-match.
Quality Measures in Biometric Systems
Biometric technology has been increasingly deployed in the past decade, offering greater security and convenience than traditional methods of personal recognition.
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.
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.
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.
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.
Handwriting Biometrics: Applications and Future Trends in e-Security and e-Health
Background- This paper summarizes the state-of-the-art and applications based on online handwritting signals with special emphasis on e-security and e-health fields.
ChildCI Framework: Analysis of Motor and Cognitive Development in Children-Computer Interaction for Age Detection
This article presents a comprehensive analysis of the different tests proposed in the recent ChildCI framework, proving its potential for generating a better understanding of children's neuromotor and cognitive development along time, as well as their possible application in other research areas such as e-Health and e-Learning.
Super-Resolution for Selfie Biometrics: Introduction and Application to Face and Iris
Such techniques are designed to restore generic images and therefore do not exploit the specific structure found in biometric images (e. g. iris or faces), which causes the solution to be sub-optimal.
Biometric Signature Verification Using Recurrent Neural Networks
Architectures based on Recurrent Neural Networks (RNNs) have been successfully applied to many different tasks such as speech or handwriting recognition with state-of-the-art results.
Fingerprint Liveness Detection Based on Quality Measures
A new fingerprint parameterization for liveness detection based on quality measures is presented.
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.
Facial Soft Biometrics for Recognition in the Wild: Recent Works, Annotation, and COTS Evaluation
The role of soft biometrics to enhance person recognition systems in unconstrained scenarios has not been extensively studied.
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.
Fingerprint Image-Quality Estimation and its Application to Multialgorithm Verification
This is also supported by numerous experiments involving a simpler quality estimator, a trained method (NFIQ), as well as the human perception of fingerprint quality on several public databases.
Quality-Based Conditional Processing in Multi-Biometrics: Application to Sensor Interoperability
We compare our fusion approach to a set of rule-based fusion schemes over normalized scores.
Periocular Biometrics: A Modality for Unconstrained Scenarios
Periocular refers to the externally visible region of the face that surrounds the eye socket.
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.
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.
Introduction to Presentation Attacks in Signature Biometrics and Recent Advances
Applications based on biometric authentication have received a lot of interest in the last years due to the breathtaking results obtained using personal traits such as face or fingerprint.
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.
Combining Blockchain and Biometrics: A Survey on Technical Aspects and a First Legal Analysis
Meanwhile, blockchain, the very attractive decentralized ledger technology, has been widely received both by the research and industry in the past years and it is being increasingly deployed nowadays in many different applications, such as money transfer, IoT, healthcare, or logistics.
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.
Synthetic Data for Face Recognition: Current State and Future Prospects
Over the past years, deep learning capabilities and the availability of large-scale training datasets advanced rapidly, leading to breakthroughs in face recognition accuracy.
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.
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.
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.
Exploring Transformers for On-Line Handwritten Signature Verification
The application of mobile biometrics as a user-friendly authentication method has increased in the last years.
LivDet2023 -- Fingerprint Liveness Detection Competition: Advancing Generalization
The International Fingerprint Liveness Detection Competition (LivDet) is a biennial event that invites academic and industry participants to prove their advancements in Fingerprint Presentation Attack Detection (PAD).
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.
Optimizing Key-Selection for Face-based One-Time Biometrics via Morphing
Nowadays, facial recognition systems are still vulnerable to adversarial attacks.
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.
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.
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.
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.
E2F-Net: Eyes-to-Face Inpainting via StyleGAN Latent Space
We further improve the StyleGAN output to find the optimal code in the latent space using a new optimization for GAN inversion technique.
SDFR: Synthetic Data for Face Recognition Competition
The submitted models were trained on existing and also new synthetic datasets and used clever methods to improve training with synthetic data.
