Past Events

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.

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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.

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.

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.

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.

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.

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.

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.

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.

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.