Past Events

The lecture will demonstrate the use of Machine Learning to improve privacy and to create and incorporate faces in video. Building blocks of such technologies will be discussed along with differences on the needs of Privacy vs. Face Recognition capabilities. The presentation will also show advances in generation of live faces and use of such technology within Synthetic Media used by the good guys (as opposed to deep-fakes). Several practical challenges of the real world vs. machine learning algorithms of various kinds and goals will be reviewed, such as guarantee for better privacy and better cost performance vs other alternatives.

Curriculum vitæ

Mickey Cohen graduated in Applied Physics from the Weizmann Institute of Science, then developed Smart Card Based PayTV user management systems with NDS (DirectTV in the USA and Sky/VideoCrypt in Europe). He has been dealing with Practical Cryptography and Information Security for over 30 years. His Biometrics expertise includes governmental identity document issuing systems for 15 years. He was a major contributor to the development of the Ecuador RFeID card, including the M.o.I software, Tanzania's biometric eDriving License, Zanzibar's biometric voter card and many more.

For the last 4 years, he also operates as GDPR and privacy expert. Additionally, he is heading the Israeli ISO delegation to standardization in Biometrics (SC37), Cyber and Privacy (SC27) and Identity Documents (SC17), and participates in many related Working Groups (WGs). He enjoys latest advances in Machine Learning and Artificial Intelligence in these fields.

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

One of the major errors from human beings, and particularly when talking about science and technology, is trying to find the unique best solution for everything. Biometrics is not a case apart, the typical question is "which is the best modality?". And when someone answers that question with "Depends!", mixed feelings between disbelief and surprise arise. In this talk, this kind of answer is going to be demonstrated in this talk, as two different biometric modalities are going to be presented, and after that they will be applied to a specific situation and context. The modalities chosen will be fingerprint and handwritten signature, both of them full of prejudices, both positive and negative. The scenario and context in which they will be applied is their application to smartphones, analysing their performance not only under laboratory conditions, but also under presentation attacks and considering deployment restrictions.

Curriculum vitæ

Prof. Raul Sanchez-Reillo obtained his PhD in Telecommunication Engineering in 2000, by Universidad Politecnica de Madrid. Currently, he is Professor at University Carlos III of Madrid (UC3M). He is also the Head of the University Group for Identification Technologies (GUTI). His R&D group is involved in project development related to identification technologies, either by the user of secure elements (such as smartcards) and/or by using Biometrics. In addition to R&D activities, he has also managed projects concerning a broad range of applications, from Social Security Services till Financial Payment Methods. He has taken part in European Projects like eEpoch, BioSec, BEST Network, EKSISTENZ, MobilePass and ORIGINS, being WP leader in most of them. He is member of SC17, SC27 and SC37 Standardization Committees. He holds the Spanish Chair in SC17 and the Spanish Secretariat in SC37, as well as the Secretariat of the international working groups SC17 WG11 and SC37 WG2. In 2009 he founded IDTestingLab, an Evaluation Laboratory for Identification Products. He is member of several ad-hoc groups such as the Biometric Vulnerability Assessment Expert Group (BVAEG).

When suspects of crimes are caught by the police, their facial images and fingerprints are recorded and added to the extensive databases they have. If on a crime scene fingermarks are found they are compared to the databases using advanced fingerprint matching algorithms and in this way it is possible to obtain a short list of suspects quickly. However, when the fingerprints are recorded at the police office, sometimes traces of other fingerprints are left on the glass plate of the fingerprint sensor. Also, sometimes, the calibration of the sensor is not performed correctly and a "negative" of the previous fingerprint is stored. The left traces are mixed with the new fingerprint forming a ghost fingerprint pattern, often called "ghost" for short. In the databases of the police such ghosts are present, but it is not known how many and how serious the effect is. Of course they interfere with the proper recognition of fingerprints, sometimes giving a wrong match, sometimes causing a failure to match a fingerprint. This presentation gives an overview of the various approaches we attempted to detect these ghost fingerprints and estimate their impact on the matching process.

Curriculum vitæ

Dr. Luuk Spreeuwers studied Electrical Engineering at the University of Twente, Netherlands. In 1992 he obtained his PhD from the University of Twente. The title of his PhD-thesis is: Image Filtering with Neural Networks: Applications and Performance Evaluation. Subsequently Luuk Spreeuwers worked at the International Institute for Aerospace and Earth Sciences (ITC) in Enschede, Netherlands, the University of Twente in a SION project on 3-D image analysis of aerial image sequences and in Budapest at the Hungarian Academy of Sciences in a 3-D textures ERCIM project. From 1999-2005 Luuk Spreeuwers worked on 3-D modeling and segmentation of the human heart in MRI at the Image Sciences Institute of the University Medical Centre in Utrecht, the Netherlands. Currently he is an Associate Professor at the Data Management and Biometrics (DMB) group at the University of Twente and is involved in projects on 2D/3D face recognition, face morphing, finger vein biometrics and others. Luuk Spreeuwers has published over 80 papers at international conferences and in journals. His expertise involves digital image processing and analysis, medical image analysis, biometrics and pattern recognition in general.

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.

Due to the imaging variabilities and to the complex nature of the face shape and dynamics, analyzing and recognizing human faces from digital images is still a very complex task.

In the last decade deep learning techniques have strongly influenced many aspects of computational vision. Many difficult vision tasks can now be performed by deploying a properly tailored and trained deep network. Oxford University’s VGG-face is possibly the first deep convolutional network designed to perform face recognition, obtaining unsurpassed performance at the time it was firstly proposed. The enthusiasm for deep learning is unfortunately paired by the present lack of a clear understanding of how they work and why they provide such brilliant performance. The same applies to Face Recognition.

Over the last years, several and more complex deep convolutional networks, trained on very large, mainly private, datasets, have been proposed still elevating the performance bar also on quite challenging public databases, such as the Janus IJB-A and IJB-B. Despite of the progress in the development of such networks, and the advance in the learning algorithms, the insight on these networks is still very limited.

For this reason, we shall analyse the neural architecture of the early stages of the human visual system to devise a biologically-inspired model for face recognition. The aim is not pushing the recognition performance further, but to better understand the representation space produced from a deep network and how it may help explaining the process undergoing a real biological neural architecture.

In this talk we analyse a hybrid model network trying to better understand the role of the different layers, including the retino-cortical mapping simulated by a log-polar image resampling. The following issues will be addressed:

• What is the representation space within a deep convolutional network and how this reflects the organization of the human visual cortex?
• How the retino-cortical mapping, implemented in the human visual system, may impact the representation space, hence improving the classification performance?
• The relevance of peripheral vs foveal vision for face recognition.

Curriculum vitæ

Massimo Tistarelli received the Phd in Computer Science and Robotics in 1991 from the University of Genoa. He is Full Professor in Computer Science (with tenure) and director of the Computer Vision Laboratory at the University of Sassari, Italy. Since 1986 he has been involved as project coordinator and task manager in several projects on computer vision and biometrics funded by the European Community.

Since 1994 he has been the director of the Computer Vision Laboratory at the Department of Communication, Computer and Systems Science of the University of Genoa, and now at the University of Sassari, leading several National and European projects on computer vision applications and image-based biometrics.

Prof. Tistarelli is a founding member of the Biosecure Foundation, which includes all major European research centers working in biometrics. His main research interests cover biological and artificial vision (particularly in the area of recognition, three-dimensional reconstruction and dynamic scene analysis), pattern recognition, biometrics, visual sensors, robotic navigation and visuo-motor coordination. He is one of the world-recognized leading researchers in the area of biometrics, especially in the field of face recognition and multimodal fusion. He is coauthor of more than 150 scientific papers in peer reviewed books, conferences and international journals. He is the principal editor for the Springer books Handbook of Remote Biometrics and Handbook of Biometrics for Forensic Science.

Prof. Tistarelli organized and chaired several world-recognized several scientific events and conferences in the area of Computer Vision and Biometrics, and he has been associate editor for several scientific journals including IEEE Transactions on PAMI, IET Biometrics, Image and Vision Computing and Pattern Recognition Letters.

Since 2003 he is the founding director for the Intl. Summer School on Biometrics (now in its 17^th edition). He is a Fellow member of the IAPR and Senior member of IEEE, and Vice President of the IEEE Biometrics Council.

The conference is focused on all technical factors affecting the deployment and use of high performance face recognition applications, including applications, standards, advanced and rapid capture, quality assessment, age and ageing effects, demographic effects, presentation attack detection, non-cooperative uses, accuracy measurement and performance tests.

More than 15 years ago, the research community claimed that fingerprints are very difficult to reproduce and steal. We lost our "innocence" when, between 2001 and 2002, some scholars fabricated artificial replicas of the fingers, named "fake fingers" or "gummy fingers", that, if put on the fingerprint sensor surface, provided images impossible to distinguish from those of the live fingers, even by visual inspection of experts.

Since the fundamental problem was the lack of data, the organization of the International Fingerprint Liveness Detection Competition, known as "LivDet", helped our research group to acquire strong know-how on the difficulties in fabricating fake fingers.

From 2015 to the 2019 edition, deep-learning-based algorithms outnumbered the ones based on handcraft features. In this webinar, we firstly review the main techniques for fingerprint presentation attack detection. We also summarize the LivDet experience. Finally, we provide some anticipations of what we expect by the incoming Livdet 2021. Our goal is to answer the following question: what did we gain, and what did we lose on moving from methods based on handcrafted features to deep learning ones? What can a possible pathway for the future of this topic be?

Curriculum vitæ

Gian Luca Marcialis is Associate Professor of Computer Engineering at the University of Cagliari, Italy. He obtained the MS degree in Electronic Engineering in 2000, and the Ph.D. degree in Computer Engineering in 2004. Since 2000 he joined the Pattern Recognition and Applications Laboratory (PRA Lab) of the Dept. of Electrical and Electronic Engineering – University of Cagliari, where he is currently director of the Lab’s Biometric Unit.

Gian Luca has published more than one hundred papers on international journals, conferences and books (H-index is 34 according to Google Scholar). His main contributions are on the multi-modal fusion of classifiers for fingerprint classification and verification, the vulnerability assessment of multiple biometric systems, face recognition, adaptive biometric systems and fingerprint liveness detection, as well as EEG signal processing.

He is involved in international and national research projects as responsible and team leader (“BullyBuster”, “Let’s Crowd”, “Tabula Rasa”) and is also Chair of the International Competition of Fingerprint Liveness Detection (LivDet).

Deepfake videos, where a person's face is automatically swapped with a face of someone else, are becoming easier to generate with more realistic results. In response to the threat such manipulations can pose to our trust in video evidence, several large datasets of deepfake videos and many methods to detect them were proposed recently. However, it is still unclear how realistic deepfake videos are for an average person and whether the algorithms are significantly better than humans at detecting them. This talk presents a subjective study conducted in a crowdsourcing-like scenario, which systematically evaluates how hard it is for humans to see if the video is deepfake or not. A subset of videos from Facebook deepfake database was used in the evaluation and its results are compared with the performance of two different state of the art deepfake detection methods, based on Xception and EfficientNets (B4 variant) neural networks.

Curriculum vitæ

Dr Pavel Korshunov is a research associate at the Idiap Research Institute. He works on detection of deepfake and audio-visual manipulations, gender recognition, speaker anti-spoofing, and speech diarization. He is one of the contributors to the signal processing and machine learning open source toolbox "Bob". Previously, he worked on problems related to high dynamic range (HDR) imaging, crowdsourcing, visual privacy, and video surveillance. He has an ACM TOMM journal best paper award (2011), two top 10 best paper awards in MMSP 2014, and a top 10 best paper award in ICIP 2014. He has over 70 research publications and is a co-editor of JPEG XT standard for HDR images.

The European Association for Biometrics is pleased to announce the launch of its Biometrics Training Event which will be held on the 17^th and 18^th September 2020 at the Fraunhofer IGD, Darmstadt, Germany, running in parallel with BIOSIG 2020.

The event aims to provide an opportunity to learn first-hand from world-leading experts both the basics of biometric systems and also the latest developments across the community. It is aimed at a wide range of stakeholders including industrial and governmental developers and end-users, researchers, academics and post-graduate students, and policy makers.

We thank our sponsor:

EAB is launching the fourteenth 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.

We thank the sponsor of this event:

All members of EAB are invited to join us for our annual General Assembly and elect the Supervisory Board for the next term of office of three years.

The 7^th edition of the EAB Research Projects Conference will take place as virtual conference from 14 to 16 September 2020. The conference is organized by the European Association on Biometrics (EAB) in cooperation with the Joint Research Center (DG JRC) of the European Commission, through its Cyber and Digital Citizens’ security Unit. The EAB-RPC 2020 will be co-located with the EAB Biometrics Research, Industry and Max-Snijder-Awards and the IEEE BIOSIG Conference, later that same week.

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.

We thank our partners:

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

Meeting of members to discuss a response to a document of the EDPS published in June 2020.

Biometrics has proven to be a very powerful technology to identify or authenticate users. The development of biometrics is also leveraging new progress in the field of Biometric sensors, Computing power and Artificial Intelligence. Beyond the reinforcement of security, user experience has become another key topics to enable the usage of biometrics in a larger number of use cases. Recent progress include the usage of Fingerprint, Face or Iris on smartphone for consumer applications. Contactless biometrics technologies contribute to improving the user experience and the maturity of existing solutions is such that they are already used in different application fields such as forensics, border control, passenger facilitation or access control. During this webinar we will show how contactless technologies improve the user experience without compromising the security and discuss the challenges and limitations. We will also present different uses cases where they have proved their efficiency in particular using Fingerprint and Face with a special focus on the performance of contact versus contactless fingerprints and their interoperability.

Curriculum vitæ

Hervé Jarosz is VP Products & Programs, Biometrics Devices for IDEMIA. He has been working with the company since 1990 and has a strong experience in the field of biometrics. He started in the company as a research scientist involved in the development of fingerprint algorithms. From 2000 he successively moved to different positions in the company such as product manager and product director biometric terminals. Hervé has a PHD in image processing.

Finger-vein, or finger vascular pattern recognition is an upcoming form biometric recognition that combines a good recognition performance with an inherent robustness against presentation attacks in the sense that it does not leave traces. The first step in the recognition process is the acquisition of a gray-scale image in which the vascular pattern is visible as dark lines. From this image relevant features are extracted for recognition. In this webinar recent work at the University of Twente will be described in which a physical model of the finger was developed. The purpose of that model is to better understand the imaging process of finger vascular patterns, leading on the longer term to better sensors and improved recognition performance. The first results give new insights in the role of soft tissue, bone and joints in the imaging process. Based on the model the group developed finger phantoms that can be used to support the development of sensors and that can provide ground truth for finger-vein detection.

Curriculum vitæ

Prof. Dr. Raymond Veldhuis is a full professor of Biometric Pattern Recognition at the University of Twente, where he leads the Data Management and Biometrics group. His main research topics are face recognition, fingerprint recognition, vascular pattern recognition, multibiometrics, and biometric template protection. The research is both applied and fundamental. Raymond Veldhuis is Editor of IEEE TIFS and chairman of the EAB Special Interest Group Academia. He has been involved in numerous national and EU projects on biometrics, of which the ITN PriMa (Privacy Matters) is the most recent. Raymond Veldhuis teaches analogue and digital signal processing as well as biometrics and pattern recognition.

"Garbage In, Garbage Out". The well-known computer science GIGO principle summarises in a very efficient and graphic manner, the pivotal role played by the soundness of the data given as input to any computerised system, in the meaningfulness of the output results. As in any other area of science, only nonsense conclusions can be expected from flawed premises. And automated biometric systems are no exception to this rule.

The current webinar will deepen into how the estimation of biometric quality and quality metrics can help to avoid the GIGO principle, how it can be measured, how can quality metrics be evaluated, and their multiple applications in biometrics.

Curriculum vitæ

Javier Galbally received the M.Sc. degree in electrical engineering from the Universidad de Cantabria, Spain, in 2005, and the Ph.D. degree in electrical engineering from the Universidad Autónoma de Madrid, Spain, in 2009, where he was an Assistant Professor until 2012. In 2013, he joined the European Commission in DG Joint Research Centre, where he is currently a Scientific/Technical Officer. His research interests are mainly focused on the security and performance evaluation of biometric systems, pattern and biometric recognition. He is actively involved in different European projects dealing with biometrics and their use in large IT systems. He is the Chair of the EAB Research Projects Conference and has authored over 100 publications mainly focused on the biometrics field.

Recent discussions on privacy protection, for instance within the framework of the EU General Data Protection Regulation (GDPR), has raised privacy concerns regarding the storage and use of biometric data. The international standard ISO/IEC 24745 has established two main requirements for protecting biometric templates i) irreversibility and ii) unlinkability back in 2011. Since then, numerous efforts have been directed to the development and analysis of irreversible templates. However, until recently, a systematic quantitative manner to analyse the unlinkability of such templates was proposed. As a consequence, the lack of a unified framework to analyse all privacy aspects of biometric template protection schemes may have hindered their further deployment.

In this presentation, we will focus on the objective and quantitative evaluation of biometric template protection schemes. To that end, the main concepts related to template protection will be introduced, together with a review of the main existing approaches. A unified framework for the evaluation and benchmarking will be subsequently described, including the recently proposed unlinkability metric and some practical examples.

Curriculum vitæ

Marta Gomez-Barrero is a Professor for IT-Security and technical data privacy at the Hochschule Ansbach, in Germany. Between 2016 and 2020, she was a postdoctoral researcher at the National Research Center for Applied Cybersecurity (ATHENE) - Hochschule Darmstadt, Germany. Before that, she received her MSc degrees in Computer Science and Mathematics (2011), and her PhD degree in Electrical Engineering (2016), all from Universidad Autonoma de Madrid, Spain.

Her current research focuses on security and privacy evaluations of biometric systems, Presentation Attack Detection (PAD) methodologies, and biometric template protection (BTP) schemes. She has co-authored more than 70 publications, chaired special sessions and competitions at international conferences, she is associate editor for the EURASIP Journal on Information Security, and represents the German Institute for Standardization (DIN) in ISO/IEC SC37 JTC1 SC37 on biometrics. She has also received a number of distinctions, including: EAB European Biometric Industry Award 2015, Best Ph.D. Thesis Award by Universidad Autonoma de Madrid 2015/16, Siew-Sngiem Best Paper Award at ICB 2015, Archimedes Award for young researches from Spanish MECD, and Best Poster Award at ICB 2013.

From the early days, when security was the driving force behind biometric research, today's challenges go far beyond security. Machine learning, Image understanding, Signal analysis, Neuroscience, Robotics, Forensic science, Digital forensics and other disciplines, converged in a truly multidisciplinary effort to devise and build advanced systems to facilitate the interpretation of signals recorded from individuals acting in a given environment. This is what we simply call today "Biometrics".

What are the most up-to-date core biometric technologies developed in the field? What is the potential impact of biometrics in forensic investigation and crime prevention? What can we learn from human perception? How to deploy current Deep Learning approaches? How to deal with adversarial attacks in biometric recognition?

This school follows the successful track of the International Summer Schools on Biometrics held since 2003. In this 17^th edition, the courses will mainly focus on new and emerging issues:

• Biometrics for social interactions and emerging applications;
• How to exploit new biometric technologies in forensic and security applications;
• Evaluation and assessment of biometric and forensic applications;
• Deep Learning for biometrics, forensic identification and Identity Science.

The courses will provide a clear and in-depth picture on the state-of-the-art in biometric verification/identification technology, both under the theoretical and scientific point of view as well as in diverse application domains.

The lectures will be given by 18 outstanding experts in the field, from both academia and industry.

An advanced feature of this summer school will be some practical sessions to better understand, "hands on", the real potential of today's biometric technologies.

Nowadays, biometrics find application as an integral component of identity management systems. The recent rapid growth of the size and popularity of such systems has prompted research into technologies which support efficient, secure, and accurate processing of large amounts of biometric data. This presentation will provide an introduction to said topics and challenges specifically associated with biometric identification (1:N search). Furthermore, examples of academic research will be presented and discussed in the context of applicability in real deployments of biometric systems.

Curriculum vitæ

Pawel Drozdowski is a researcher with the Faculty of Computer Science, Hochschule Darmstadt, Germany, where he works on research projects in the context of the National Research Center for Applied Cybersecurity ATHENE. His interests within biometrics include efficient algorithmic solutions for large-scale database searches, information fusion, privacy and template protection, as well as ethical aspects of such systems, especially concerning demographic bias and fairness. He co-authored more than 20 scientific publications in the field of biometrics and represents the German Institute for Standardization (DIN) in ISO/IEC SC37 JTC1 SC37 on biometrics.

Widespread deployment of Automatic Border Control (ABC), along with electronic Machine Readable Travel Documents (eMRTD) for person verification, has enabled a prominent use case of face biometrics in border control applications. The trust anchor are biometric passports.

Many countries issue eMRTD passports on the basis of a printed biometric face photo submitted by the applicant, a procedure which allows the possibility of the photo being either altered to beautify the subject’s appearance or morphed to conceal his/her identity.

If an eMRTD passport is issued with a morphed facial image, two or more data subjects can then use it to pass a border control. This talk will present the state of the art of Morphing Attack Detection (MAD) and discuss the challenges associated with this research. Further the mid term research agenda will be indicated.

Curriculum vitæ

Christoph Busch is chairing the Norwegian Biometrics Lab (NBL) at the Norwegian University of Science and Technology (NTNU), Norway. He holds a joint appointment at the Hochschule Darmstadt (HDA), Germany and, since 2007, he lectures biometric systems at the Technical University of Denmark.

Christoph has coordinated series of projects for the German Federal Office for Information Security (BSI), including BioIS, BioFace, BioFinger, BioKeyS Pilot-DB, KBEinweg and NFIQ2.0, and contributed to 3D-Face, FIDELITY, TURBINE, ORIGINS, INGRESS, SOTAMD and others EU projects.

He is also principal investigator at the German National Center for Applied Cybersecurity (ATHENE) and a co-founder of the European Association for Biometrics. Christoph has co-authored over 400 technical papers and spoken at numerous international conferences.

He is associate editor for the IET Biometrics and IEEE Transactions on Information Forensics and Security journals, chairs the TeleTrusT Biometrics Working Group and German standardisation body on biometrics, and is also convenor of WG3 in ISO/IEC JTC1 SC37.

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.

The 2020 International Workshop on Biometrics and Forensics (IWBF 2020) is jointly organized by the Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) & the Norwegian University of Science and Technology (NTNU) and will be held at Porto, Portugal, on April 29-30, 2020. IWBF is an international forum devoted to facilitating synergies in research and development among the areas of multimedia forensics, forensic biometrics, and forensic science. IWBF provides the meeting place for those concerned with the use of advanced biometric technologies in forensic applications, attracting participants from industry, research, academia, and end-users.

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

The ProfitCard also looks at the latest trends in 2020, with the main topics on the agenda being mobile payment, electronic identity and payments in times of PSD2.

The electronic identification of customers is one of the decisive influencing factors for the further development of existing business models and the development of new ones in the future. The ProfitCard provides up-to-date information on projects already underway and offers a glimpse into the future.

Individual banks will report on the consequences that digitization will have for their respective business models, how customer relationships will change and what effects this will have on cost and revenue structures.

Since September 14, 2019, online payments must be secured with strong customer authentication – as stipulated by the European Payment Services Directive (PSD2). The postponement granted by the European banking regulator until the end of 2020 for some cases does not alter the fact that this will have an impact on the payment methods offered by online merchants and their use by customers.

The ProfitCard offers first-hand insider knowledge and excellent networking with decision-makers and designers in the industry.

Idiap Research Institute and the European Association for Biometrics EAB are organizing the first EAB Winter Workshop on Presentation Attack Detection evaluation and certification. The aim of the workshop is to bring together researchers, companies, customers, practitioners in biometrics to present latest research findings and challenges in Presentation Attack Detection, to unveil industrial solutions and to discuss the need for evaluation and certification. The workshop will start with an half-a-day introduction to biometrics and presentation attack detection taylored for beginners. The second day will be dedicated to scientific presentations, industrial spotlights with demonstrations and networking.

Industry demonstrations will be provided by Cognitec, TECH5, BioID, MOBAI, OneVisage and ams.

We thank our sponsors for this event: