Past Events

Workshop of the Biometrics Working Group of TeleTrusT, the IT Security Association in Germany

For the purpose of transparency and reproducibility, The Danish National ID Centre has developed a data model to assist the facial examiner in placement on the conclusion/opinion scale. By processing case data, including suitability for comparison, image quality and levels of visibility, the model supports the manual facial examination. The aim of the model is to introduce limitations to the subjective evaluation of a face comparison, by introducing overall objective parameters into the decision through the data model.

Curriculum vitæ

Trine Edvardsen is an experienced biometric analyst within the fields of facial and fingerprint examinations. In the Danish National ID Centre, she has been involved in the innovation and advancement of the facial examination procedures used by the biometric team. She is also a member of FISWG and FINWG. Trine has a background in the natural sciences, with a PhD in palaeontology from The Natural History Museum of Denmark and a postdoc from the University of Exeter.

We thank our media partner:

The IFPC 2022, takes place virtually, from November 15 until 17, 2022. The IFPC focuses on all technical factors affecting the deployment and use of high performance face recognition applications, including applications,standards, quality assessment,human aspects,demographic aspects, demographic effects, age and ageing effects, presentation attack detection, morphing datasets, their preparation, training and tuning, non-cooperative uses, accuracy measurement, and performance tests.

With support of the Department of Homeland Security's Science and Technology Directorate, the conference aims to assemble speakers from all over the world involved in face recognition development, procurement, deployment as well as operations. The main aim of the IFPC is to bring greater maturity to face recognition by improving performance, transparency and trustworthiness. Furthermore, during this event,speakers have the opportunity to present proposals for technical or policy presentations which address problems that might influence face recognition operations and applications.The IFPC focuses on improving relevant factors concerning face recognition, including performance, transparency and trustworthiness.

Using our face as a key to unlock our mobile devices has become ubiquitous, as we love the simplicity and security that face recognition technology can bring to us when verifying our identity in a digitalized society. And our face is unique and remains consistent in a long period, we do not want our facial data to be misused while we are enjoying the benefits from face recognition technology. In this talk, Erik Guoqiang Li will share his experience and knowledge on how to secure privacy and compliance when deploying a face recognition based authentication system in different use-cases (e.g. Identity Proofing, Verifiable Credential, etc.). He will also discuss the technology and solutions developed by Mobai to meet the requirements specified by different regulators and standards.

Curriculum vitæ

Dr. Erik Guoqiang Li obtained his PhD degree with research work focusing on fingerprint recognition from Norwegian University of Technology and Science (NTNU) in 2016. Since the start of his PhD program in 2012, he has participated in four European Commission funded projects (FIDELITY, PIDaaS, SOTAMD, iMARS) as well as leading several research projects funded by the Research Council of Norway. He has been working on various research topics in biometrics field: fingerprint recognition, face recognition, biometric template protection, behavioural biometrics. Since the beginning of 2020, he joined Mobai AS as the director of R&D whilst he also works as an adjunct research fellow at NTNU.

We thank our media partner:

Bloom filters (BFs) and homomorphic encryption (HE) are prominent techniques used to design biometric template protection (BTP) schemes that aim to protect sensitive biometric information during storage and comparison. In this talk, Amina will discuss the strengths and weaknesses of these two approaches. Her key insight is to extend this theoretical investigation to iris recognition, which 1) benefits from the alignment-free property of BFs and 2) induces huge computational burdens in the HE-encrypted domain. BF-based BTPs can be fast with high recognition accuracy but lack unlinkability, or fast with unlinkability but lack high accuracy. HE-based BTPs are secure, accurate, and unlinkable, but slower than BF-based approaches. In light of a joint work recently published in the IET Biometrics journal in 2022, Amina will present her hybrid BTP scheme that combines BFs and HE as a solution that ensures unlinkability and high recognition accuracy while being seven times faster than the traditional HE-based approach.

Curriculum vitæ

Amina Bassit received her BSc degree in discrete mathematics from Hassan II University (2013) and her MSc degree in cryptography from both Mohammed V University and Limoges University (2015). She was employed as a cryptographer at the DGSSI Morocco (2016-2019). Since April 2019, Amina has joined the DMB group and the SCS group of the University of Twente to design a biometric verification protocol in the encrypted domain. In May 2020, Amina started her Ph.D. as part of the PriMa (Privacy Matters) project, where she is investigating the integration of biometric recognition and homomorphic encryption with a special interest in security against malicious adversaries.

We thank our media partner:

Businesses lose billions of dollars every year to fraud and have put in place measures that destroy customer experience. People waste one year of their lives in cumbersome authentication processes for everyday tasks, such as opening a bank account, checking in at a hotel, paying for goods or recovering passwords for their online accounts. Both security and user experience can improve dramatically via face authentication. The main challenge so far has been how protect user data, especially personal identifiable information. YooniK makes it possible for anyone to authenticate themselves to devices they don’t trust without ever sharing a single bit of biometric information. YooniK's self-sovereign decentralized vision of authentication entails issuers, who will be able to create verifiable credentials for any process, and verifiers, who will be able to check those credentials and obtain proofs to user claims. And the broker is the user Face Wallet, sitting on their phone, which allows any connected device with a camera to see their face and obtain the right consented credentials to make that process work without ever providing companies or YooniK access to user biometrics.

Curriculum vitæ

With 20 years of experience in technology, innovation and product design, from large telco companies to medium-size companies and start-ups, and a strong research background, Pedro Torres has worked for the last seven years in global executive positions in customer experiences based on biometrics to enable immersive and seamless journeys. 

A strong believer in decentralised self-sovereign approaches to privacy, Pedro has been leading efforts to provide the necessary protection and control to users as they authenticate for convenience with their face in multiple services such as proving identity to create a bank account, automatically checking-in to hotels, picking up car rentals or pay for goods and use loyalty in a fully contactless on-the-move fashion.

 With a solid background in Machine Learning with PhD research in Artificial Intelligence at Imperial College London, Computer Diploma from the University of Cambridge and various scientific publications in peer reviewed journals, Pedro has recently co-founded YooniK to disrupt the world of private authentication.

We thank our media partner:

The Norwegian Biometric Forum (NBF) is an open platform dedicated to regular exchange of information and experience related to the field of Biometrics. The target of the group is the interdisciplinary discussion between research, technology developers, data privacy experts, governmental agencies and operators of Biometric Systems. In the regular meetings new applications, latest research results and products are presented.

More information will be provided shortly.

We thank our media partner:

EAB is launching the sixteenth European Biometric Max Snijder, Research, and Industry Awards. These prestigious awards are granted annually to individuals who have been judged by a panel of internationally respected experts to be making a significant contribution to the field of biometrics research in Europe.

GOLD sponsors of this event:

We thank our media partner:

All members of EAB are invited to join us for our annual General Assembly.

The 9^th edition of the EAB Research Projects Conference is organised by the European Association on Biometrics (EAB) with the contribution of eu-LISA through its Governance and Capabilities Unit, the support of DG HOME of the European Commission, Fraunhofer IGD and Halmstad University.

The conference is currently the largest event on research funded by the European Union in the area of Biometrics and Identity Management. Over the previous successful editions, EAB-RPC has become the main forum in Europe where attendees can simultaneously: promote research carried out in biometrics, forge new links and networks, and identify the appropriate partners for possible future project applications. Last year’s edition welcomed over 100 participants from academia, industry and public institutions.

Sponsor of this event:

We thank our contributors:

We thank our media partner:

Workshop of the Biometrics Working Group of TeleTrusT, the IT Security Association in Germany

Digital face manipulation has become a thriving topic in the last few years, especially after the popularity of the term DeepFakes. Traditionally, the number and realism of digital face manipulations have been limited by the lack of sophisticated editing tools, the domain expertise required, and the complex and time-consuming process involved. Nowadays, it is becoming increasingly easy to manipulate pictures and videos, thanks to: the accessibility to large-scale public data and the evolution of deep learning techniques. As a result, open software and mobile applications opened the door to anyone to create fake images and videos, without any experience in the field.

The EAB organizes this two day virtual event with The Handbook “Digital Face Manipulation and Detection” as guideline. The workshop will feature presentations by the authors of this Handbook. They combine both biometrics and media forensic fields. The event is aimed at everyone who is interested in digital face manipulation from the point of view from both academic institutions and industry.

The aim of the event is to inform about this topic, and to give a well-rounded understanding of the current developments, as well as to discuss how to detect face manipulations, and current and future challenges in digital face manipulation.

Sponsor of this event:

We thank our media partner:

A 2-day programme will cover subjects such as: remote biometrics, inconsistencies in the current proposal, the European Commission’s expectation from the standardisation activity, JTC1 and ISO/IEC 9868.

Sponsor of this event:

We thank our media partner:

For the past two decades, researchers have been working to fulfil the promise of ECG biometrics. While face can be stolen at a distance and fingerprints are left everywhere, the electrocardiogram would be the hidden secret to fight spoofing and counterfeiting. We just needed to develop systems as accurate, robust, and unobtrusive as those available for more developed traits. However, after twenty years and plenty of literature, we still aren’t there yet. Acquisition setups have never been more comfortable, deep learning brought us the most sophisticated models, and databases are unprecedentedly large and complete. So, what’s missing? This is the question João aims to answer in this talk, as he walks through the history of ECG biometrics and discuss future possibilities.

Curriculum vitæ

João Ribeiro Pinto received his M.Sc. in Bioengineering (field of Biomedical Engineering) from the University of Porto in 2017, with a thesis on the use of the electrocardiogram (ECG) for biometric recognition of vehicle drivers. He is currently pursuing his Ph.D. degree in Electrical and Computer Engineering at the same university, focused on the use of ECG, face, and other data for seamless and continuous biometric recognition and wellbeing monitoring, especially for drivers/passengers inside intelligent vehicles. João has co-authored over thirty publications in biometrics and several other topics related to machine learning and pattern recognition, which have been cited over three hundred times by his peers.

We thank our media partner:

The Norwegian Biometrics Forum (NBF) is an open platform dedicated to regular exchange of information and experience related to the field of Biometrics. The target of the group is the interdisciplinary discussion between research, technology developers, data privacy experts, governmental agencies and operators of Biometric Systems. In the regular meetings new applications, latest research results and products are presented.

Victor Gomis will give a presentation about his research in relation to fraud prevention using AI-Biometrics. As Victor contends, fraudsters and their schemes will probably never cease to exist. In fact, the problem is only getting worse. Given that identity theft and account takeovers are the methods of choice for today’s back bad actors, customers’ authentication has never been more important.

Curriculum vitæ

Passionate for technology and excellent communication. Victor has over 10 years of experience in the security and biometrics market. Furthermore, he is specialized in identity theft and transactional fraud, helping companies and organizations in EMEA to enhance security in all customer engagement channels while reducing customer friction.

We thank our media partner:

Giulia Orrù will present about "Adaptive Biometric Systems in the Deep Learning Era". In the previous decade, several "adaptive" systems have been proposed to address the issue of intra-class variations in face recognition (FR) systems. In particular, novel template-based self-update algorithms, capable of retaining the expressive power of a restricted number of templates across time, allow overcoming the problem of manual updating and high computational complexity of traditional self-update. Giulia's talk aims to investigate if and to what degree "optimal" self-update algorithms enhance FR performance, particularly in application scenarios where the facial trait varies dramatically over time and the high representativeness of the deep features may not be sufficient.

Curriculum vitæ

Giulia Orrù received her M.S. degree and PhD degree in Telecommunication and Computer Science Engineering from the University of Cagliari, Italy, in 2017 and 2021, respectively. She is currently an Assistant Professor of Computer Engineering at the University of Cagliari, Italy. Since 2014 she collaborates with the Pattern Recognition and Applications Laboratory research group working on pattern recognition and its applications, specifically on biometric recognition, presentation attack detection systems and adaptive biometric systems.

We thank our media partner:

Tuğçe Arican from the University of Twente, will present her research about "Patch-Based Finger Vein Recognition Using an Auto Encoder". Auto Encoders are neural networks that use unsupervised learning methods, and aim to reconstruct their input through a series of compression and de-compression steps. Tuğçe will shed light on how the model learns a compact representation of the input, without the need of labeled data, during this process. Furthermore, Tuğçe stresses the convenience of this property if ground truth labels are hard-to-realize for large data sets, such as for finger vein data. The compact representation can be regarded as a feature vector which can be used to compare finger vein images. The contrast of veins in the images is very low. Therefore, instead of the full image, small finger vein patches will be utilized as an input to the Auto Encoder.

Curriculum vitæ

Tuğçe is a PhD.candidate at the University of Twente, at the Data Management Biometrics Group. She obtained her Bachelor degree in Computer Engineering at the Osmangazi University of Turkey. She was likewise granted with a scholarship provided by the Republic of Turkey Ministry of Education. She moved to Enschede and pursued a Masters degree in Computer Science at the University of Twente. Currently, Tuğçe is conducting research on finger vein recognition using unsupervised learning methods.

We thank our media partner:

This Virtual Lunch Talk gives a technical introduction and overview on optical 3D imaging technology. Furthermore, it is shown how this contactless technology can be used to scan biometric features of human skin tissue surfaces. The possibilities of this technology are demonstrated with special emphasis on the advancements compared to contact-based solutions. Finally, an outlook is given on how this technology can be applied in different situations where traditional technology failed so far.

Curriculum vitæ

Tom Michalsky studied physics at the Universität Leipzig, Germany, from 2007 to 2012 and received his PhD (Dr. rer. nat.) in the field of light–matter interaction in 2018. Following, he worked as a project leader in the research and development department of a commercial biometrics company in Jena, Germany, until 2021. Tom Michalsky is co-founder of IDloop, a Jena-based start-up dedicated to take 3D imaging technology to the next level by developing novel concepts for contactless recording of biometric features.

We thank our media partner:

Workshop of the Biometrics Working Group of TeleTrusT, the IT Security Association in Germany

Biometric recognition and presentation attack detection (PAD) methods strongly rely on deep learning algorithms. Though often more accurate, these models operate as complex black boxes. Interpretability tools are being used to delve deeper into the operation of these methods and we advocate their integration in the PAD scenario.The work presented will focus on face PAD CNN-based models analysis through evaluation with traditional PAD metrics and with interpretability tools. We will go through the topic and recent works that confirm the urge to establish new approaches in biometrics that incorporate interpretability tools

Curriculum vitæ

Ana F. Sequeira is a researcher focused on Computer Vision and Machine Intelligence for BIOMETRICS. Currently, at INESC TEC, Porto, Portugal; previously at IrisGuard UK Ltd, UK; and at University of Reading, UK. Holds a PhD in Electrical and Computing Engineering; a MSc and a Degree in Mathematics, all from the University of Porto. Ana’s research comprises xAI for biometrics; liveness detection; biometric recognition for border control; as well as facial analysis topics, such as emotion recognition; among others.Ana led the construction of biometric databases; managed biometric competitions and co-authored research publications.

We thank our media partner:

Back in spring 2011 our Norwegian Biometrics Laboratory (NBL) was established and for the opening we organized a workshop. Since then we have celebrated the NBL Annual Workshops (NBLAW). All the workshops are listed on the NBL homepage.

Behavioural biometrics analyses how humans perform a specific task and then tries to authenticate or identify a person based on their behaviour. Examples are signature recognition, voice recognition, gait and keystroke dynamics, but many more exist. Analysis of the human behaviour (behavioural analysis) has a lot in common with behavioural biometrics, but the main goal is not purely the identification or authentication of a person. In the NBL Annual Workshop of 2022, there are a number of speakers that will discuss various aspects of behavioural analysis, like pros and cons, or how and where it is used (or can be used) in practice. There will be speakers from academia, governmental organizations and as well as commercial organizations to shed their light on the use of behavioural analysis.  The workshop will be a fully online event via Zoom.

All times refer to CET.

Suddenly, deepfakes are questioning the integrity of automated identity verification, which undeniably is the way to go for securing trust and efficiency in our digitized world. With money laundering and identity theft at stake, sophisticated anti-spoofing measures are required. While liveness detection is a trusted mechanism to secure the real user’s presence, deepfakes are now creating new attack vectors. What are deepfakes even and what can biometrics do against them? And are they the real challenge for identity verification?

Curriculum vitæ

Coming from Fraunhofer Institute, where Ann-Kathrin Freiberg started her career during her Master studies, she has taken a deep-dive into the biometrics and identity verification industry during the last 4 years at BioID. Today, her aim is to solve the market’s pain concerning trust in remote processes. She brings new identity and authentication projects to life and supports customers with leveraging facial verification and liveness detection in their solutions. As the interface between R&D at BioID and companies from almost every industry, Ann-Kathrin works on resolving the challenges around the integration of biometrics to bring forward innovation and trust.

We thank our media partner:

PriMa (Privacy Matters) is an Innovative Training Network (ITN) funded by the EU through the Horizon 2020 Framework. PriMa is a collaboration between 7 research locations and 7 industrial partner organisations with a focus on the analysis and mitigation of privacy risks in a rapidly digitalising society.

The presentation focuses on the concept of algorithms which seeks to remove the influences of skin diseases in fingerprint recognition processes.

Curriculum vitæ

Mona Heidari of Brno University of Technology, conducted Ph.D. research concerning the analysis of diseases and other influences affecting fingerprints. Generating a large volume dataset of a synthetic diseased fingerprint and trying both classical and machine learning/deep learning approaches to detect and recognise diseases in a fingerprint image.

We thank our media partner:

The xAI4Biometrics Workshop aims at promoting a better understanding, through explainability and interpretability, of currently common and accepted practices in several and varied applications of biometrics. These applications, in scenarios comprising identity verification for access/border control, watching lists surveillance, anti-spoofing measures embedded in biometric recognition systems, forensic applications, among many others, affect the daily life of an ever-growing population.