Arjan Kuijper

Arjan Kuijper
Fraunhofer Institute for Computer Graphics Research IGD | IGD · Computer Science

Prof Dr

About

467
Publications
102,987
Reads
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5,001
Citations
Citations since 2016
242 Research Items
3607 Citations
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Introduction
Computer Vision, Computer Graphics, HCI, Machine Learning, Mathematical models, PDEs, Symmetry Sets, Black Math
Additional affiliations
August 2015 - present
Technische Universität Darmstadt
Position
  • Professor
April 2010 - July 2015
Technische Universität Darmstadt
Position
  • Privat Dozent
November 2008 - present
Fraunhofer Institute for Computer Graphics Research IGD
Position
  • Research Coach
Education
December 2009 - December 2009
Graz University of Technology
Field of study
  • Applied CS
October 1997 - June 2002
Utrecht University
Field of study
  • CS & Math
September 1989 - December 2005
University of Twente
Field of study
  • applied mathe

Publications

Publications (467)
Preprint
Full-text available
Face Recognition (FR) is increasingly used in critical verification decisions and thus, there is a need for assessing the trustworthiness of such decisions. The confidence of a decision is often based on the overall performance of the model or on the image quality. We propose to propagate model uncertainties to scores and decisions in an effort to...
Chapter
In this extended version of the paper “Linoc: A Prototyping Platform for Capacitive and Passive Electrical Field Sensing” [15], the Linoc prototyping toolkit is presented in more detail, accompanied by evaluations and recent adaptations in research projects. Central to the Linoc Toolkit are the two capacitive and the two Electric Potential Sensing...
Preprint
Full-text available
Face presentation attack detection (PAD) is critical to secure face recognition (FR) applications from presentation attacks. FR performance has been shown to be unfair to certain demographic and non-demographic groups. However, the fairness of face PAD is an understudied issue, mainly due to the lack of appropriately annotated data. To address this...
Article
Full-text available
Passive electric field sensing can be utilized in a wide variety of application areas, although it has certain limitations. In order to better understand what these limitations are and how countervailing measures to these limitations could be implemented, this paper contributes an in-depth discussion of problems with passive electric field sensing...
Preprint
Full-text available
Deep learning-based face recognition models follow the common trend in deep neural networks by utilizing full-precision floating-point networks with high computational costs. Deploying such networks in use-cases constrained by computational requirements is often infeasible due to the large memory required by the full-precision model. Previous compa...
Article
Full-text available
The recent COVID‐19 pandemic has increased the focus on hygienic and contactless identity verification methods. However, the pandemic led to the wide use of face masks, essential to keep the pandemic under control. The effect of wearing a mask on face recognition (FR) in a collaborative environment is a currently sensitive yet understudied issue. R...
Article
Full-text available
Heterogeneous cyberattacks against industrial control systems (ICSs) have had a strong impact on the physical world in recent decades. Connecting devices to the internet enables new attack surfaces for attackers. The intrusion of ICSs, such as the manipulation of industrial sensory or actuator data, can be the cause for anomalous ICS behaviors. Thi...
Preprint
Full-text available
A MasterFace is a face image that can successfully match against a large portion of the population. Since their generation does not require access to the information of the enrolled subjects, MasterFace attacks represent a potential security risk for widely-used face recognition systems. Previous works proposed methods for generating such images an...
Article
Full-text available
This work addresses the challenge of building an accurate and generalizable periocular recognition model with a small number of learnable parameters. Deeper (larger) models are typically more capable of learning complex information. For this reason, knowledge distillation (kd) was previously proposed to carry this knowledge from a large model (teac...
Article
Full-text available
Iris Presentation Attack Detection (PAD) algorithms address the vulnerability of iris recognition systems to presentation attacks. With the great success of deep learning methods in various computer vision fields, neural network-based iris PAD algorithms emerged. However, most PAD networks suffer from overfitting due to insufficient iris data varia...
Article
Full-text available
Deep neural networks have rapidly become the mainstream method for face recognition (FR). However, this limits the deployment of such models that contain an extremely large number of parameters to embedded and low-end devices. In this work, we present an extremely lightweight and accurate FR solution, namely PocketNet. We utilize neural architectur...
Article
Full-text available
Anomaly detection in smart environments is important when dealing with rare events, which can be safety-critical to individuals or infrastructure. Safety-critical means in this case, that these events can be a threat to the safety of individuals (e.g. a person falling to the ground) or to the security of infrastructure (e.g. unauthorized access to...
Article
Full-text available
Bias and fairness of biometric algorithms have been key topics of research in recent years, mainly due to the societal, legal and ethical implications of potentially unfair decisions made by automated decision-making models. A considerable amount of work has been done on this topic across different biometric modalities, aiming at better understandi...
Article
The estimation of blur kernel is the first and principal steps in the deconvolution of single blurred image. The quality of image restoration highly depends on its estimation accuracy. We then propose a new modified-Radon-transform approach along with a low-high-pass filtering method to estimate the motion blur parameters by a self-adaptive learnin...
Article
Using the face as a biometric identity trait is motivated by the contactless nature of the capture process and the high accuracy of the recognition algorithms. After the current COVID-19 pandemic, wearing a face mask has been imposed in public places to keep the pandemic under control. However, face occlusion due to wearing a mask presents an emerg...
Preprint
Full-text available
Face recognition systems have to deal with large variabilities (such as different poses, illuminations, and expressions) that might lead to incorrect matching decisions. These variabilities can be measured in terms of face image quality which is defined over the utility of a sample for recognition. Previous works on face recognition either do not e...
Preprint
Full-text available
Wearing a mask has proven to be one of the most effective ways to prevent the transmission of SARS-CoV-2 coronavirus. However, wearing a mask poses challenges for different face recognition tasks and raises concerns about the performance of masked face presentation detection (PAD). The main issues facing the mask face PAD are the wrongly classified...
Preprint
Full-text available
An essential factor to achieve high performance in face recognition systems is the quality of its samples. Since these systems are involved in various daily life there is a strong need of making face recognition processes understandable for humans. In this work, we introduce the concept of pixel-level face image quality that determines the utility...
Article
Face masks have become one of the main methods for reducing the transmission of COVID-19. This makes face recognition (FR) a challenging task because masks hide several discriminative features of faces. Moreover, face presentation attack detection (PAD) is crucial to ensure the security of FR systems. In contrast to the growing number of masked FR...
Preprint
Full-text available
Learning discriminative face features plays a major role in building high-performing face recognition models. The recent state-of-the-art face recognition solutions proposed to incorporate a fixed penalty margin on commonly used classification loss function, softmax loss, in the normalized hypersphere to increase the discriminative power of face re...
Preprint
Full-text available
With the increased deployment of face recognition systems in our daily lives, face presentation attack detection (PAD) is attracting a lot of attention and playing a key role in securing face recognition systems. Despite the great performance achieved by the hand-crafted and deep learning based methods in intra-dataset evaluations, the performance...
Article
Full-text available
Face recognition (FR) systems have a growing effect on critical decision-making processes. Recent works have shown that FR solutions show strong performance differences based on the user’s 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 demogr...
Article
Full-text available
Face recognition is an essential technology in our daily lives as a contactless and convenient method of accurate identity verification. Processes such as secure login to electronic devices or identity verification at automatic border control gates are increasingly dependent on such technologies. The recent COVID-19 pandemic has increased the focus...
Preprint
Full-text available
Deep neural networks have rapidly become the mainstream method for face recognition. However, deploying such models that contain an extremely large number of parameters to embedded devices or in application scenarios with limited memory footprint is challenging. In this work, we present an extremely lightweight and accurate face recognition solutio...
Preprint
Full-text available
A face morphing attack image can be verified to multiple identities, making this attack a major vulnerability to processes based on identity verification, such as border checks. Different methods have been proposed to detect face morphing attacks, however, with low generalizability to unexpected post-morphing processes. A major post-morphing proces...
Preprint
Full-text available
Face morphing attacks aim at creating face images that are verifiable to be the face of multiple identities, which can lead to building faulty identity links in operations like border checks. While creating a morphed face detector (MFD), training on all possible attack types is essential to achieve good detection performance. Therefore, investigati...
Conference Paper
Full-text available
For iris recognition in non-cooperative environments, iris segmentation has been regarded as the first most important challenge still open to the biometric community, affecting all downstream tasks from normalization to recognition. In recent years, deep learning technologies have gained significant popularity among various computer vision tasks an...
Preprint
Full-text available
In this paper, we present a set of extremely efficient and high throughput models for accurate face verification, MixFaceNets which are inspired by Mixed Depthwise Convolutional Kernels. Extensive experiment evaluations on Label Face in the Wild (LFW), Age-DB, MegaFace, and IARPA Janus Benchmarks IJB-B and IJB-C datasets have shown the effectivenes...
Article
Full-text available
Biometric recognition technology has made significant advances over the last decade and is now used across a number of services and applications. However, this widespread deployment has also resulted in privacy concerns and evolving societal expectations about the appropriate use of the technology. For example, the ability to automatically extract...
Article
Full-text available
Soft-biometrics play an important role in face biometrics and related fields since these might lead to biased performances, threaten the user’s privacy, or are valuable for commercial aspects. Current face databases are specifically constructed for the development of face recognition applications. Consequently, these databases contain a large numbe...
Article
Full-text available
The success of modern face recognition systems is based on the advances of deeply-learned features. These embeddings aim to encode the identity of an individual such that these can be used for recognition. However, recent works have shown that more information beyond the user’s identity is stored in these embeddings, such as demographics, image cha...
Preprint
Full-text available
This paper presents a summary of the Masked Face Recognition Competitions (MFR) held within the 2021 International Joint Conference on Biometrics (IJCB 2021). The competition attracted a total of 10 participating teams with valid submissions. The affiliations of these teams are diverse and associated with academia and industry in nine different cou...
Preprint
Full-text available
Iris presentation attack detection (PAD) plays a vital role in iris recognition systems. Most existing CNN-based iris PAD solutions 1) perform only binary label supervision during the training of CNNs, serving global information learning but weakening the capture of local discriminative features, 2) prefer the stacked deeper convolutions or expert-...
Preprint
Full-text available
An essential factor to achieve high accuracies in fingerprint recognition systems is the quality of its samples. Previous works mainly proposed supervised solutions based on image properties that neglects the minutiae extraction process, despite that most fingerprint recognition techniques are based on detected minutiae. Consequently, a fingerprint...
Chapter
Full-text available
In previous works, a mobile application was developed using an unmodified commercial smartphone to recognize whole-body exercises. The working principle was based on the ultrasound Doppler sensing with the device built-in hardware. Applying such a lab environment trained model on realistic application variations causes a significant drop in perform...
Preprint
Full-text available
The ongoing COVID-19 pandemic has lead to massive public health issues. Face masks have become one of the most efficient ways to reduce coronavirus transmission. This makes face recognition (FR) a challenging task as several discriminative features are hidden. Moreover, face presentation attack detection (PAD) is crucial to ensure the security of F...
Preprint
Full-text available
Using the face as a biometric identity trait is motivated by the contactless nature of the capture process and the high accuracy of the recognition algorithms. After the current COVID-19 pandemic, wearing a face mask has been imposed in public places to keep the pandemic under control. However, face occlusion due to wearing a mask presents an emerg...
Preprint
Full-text available
The recent COVID-19 pandemic has increased the focus on hygienic and contactless identity verification methods. However, the pandemic led to the wide use of face masks, essential to keep the pandemic under control. The effect of wearing a mask on face recognition in a collaborative environment is currently sensitive yet understudied issue. Recent r...
Preprint
Full-text available
Face recognition (FR) systems have a growing effect on critical decision-making processes. Recent works have shown that FR solutions show strong performance differences based on the user's 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 demogr...
Article
Tracking multiple persons is a challenging task especially when persons move in groups and occlude one another. Existing research have investigated the problems of group division and segmentation; however, lacking overall person-group topology modeling limits the ability to handle complex person and group dynamics. We propose a Graphical Social Top...
Chapter
A face morphing attack image can be verified to multiple identities, making this attack a major vulnerability to processes based on identity verification, such as border checks. Various methods have been proposed to detect face morphing attacks, however, with low generalizability to unexpected post-morphing processes. A major post-morphing process...
Chapter
Full-text available
Face morphing attacks aim at creating face images that are verifiable to be the face of multiple identities, which can lead to building faulty identity links in operations like border checks. While creating a morphed face detector (MFD), training on all possible attack types is essential to achieve good detection performance. Therefore, investigati...
Preprint
Full-text available
The ability to interpret decisions taken by Machine Learning (ML) models is fundamental to encourage trust and reliability in different practical applications. Recent interpretation strategies focus on human understanding of the underlying decision mechanisms of the complex ML models. However, these strategies are restricted by the subjective biase...
Article
Due to the deforming and dynamically changing textile fibers, the quality assurance of cleaned industrial textiles is still a mostly manual task. Usually, textiles need to be spread flat, in order to detect defects using computer vision inspection methods. Already known methods for detecting defects on such inhomogeneous, voluminous surfaces use ma...