Florian Kirchbuchner

Scopus Publications

Ubiquitous multi-occupant detection in smart environments
Daniel Fährmann, Fadi Boutros, Philipp Kubon, Florian Kirchbuchner, Arjan Kuijper, Naser Damer
Neural Computing and Applications, 2024
Recent advancements in ubiquitous computing have emphasized the need for privacy-preserving occupancy detection in smart environments to enhance security. This work presents a novel occupancy detection solution utilizing privacy-aware sensing technologies. The solution analyzes time-series data to detect not only occupancy as a binary problem, but also determines whether one or multiple individuals are present in an indoor environment. On three real-world datasets, our models outperformed various state-of-the-art algorithms, achieving F1-scores up to 94.91% in single-occupancy detection and a macro F1-score of 91.55% in multi-occupancy detection. This makes our approach a promising solution for improving security in smart environments.
Artificial intelligence in everyday clinical and nursing care
Medizintechnik Cologne, 2024
VeinXam: A Low-Cost Deep Veins Function Assessment
Vincent Abt, Julian von Wilmsdorff, Silvia Faquiri, Florian Kirchbuchner
Ubicomp Iswc 2023 Adjunct Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2023 ACM International Symposium on Wearable Computing, 2023
A venous insufficiency, to which the deep veins of the lower human extremities are particularly susceptible, can lead to serious diseases, such as a deep vein thrombosis (DVT) with subsequent risks of severe implications, e.g. pulmonary embolism or a post-thrombotic syndrome (PTS) [6]. The current standard procedure to diagnose venous insufficiency is performed exclusively in medical offices and hospitals in the form of in-patient treatments with special medical equipment. This hurdle for the patient, combined with the often diffuse symptoms of venous insufficiency [7], may lead to a late discovery of diseases such as DVTs and increases the risk of secondary diseases as well as treatment costs [3]. To address these issues, we propose a novel method for continuous monitoring of the current venous function by adapting the Light Reflection Rheography (LLR) and using low-cost wearable sensor technology and a smartphone app, aiming to deliver critical early stage information about pathological changes of the blood flow in the lower limbs.
Pixel-Level Face Image Quality Assessment for Explainable Face Recognition
Philipp Terhörst, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper
IEEE Transactions on Biometrics Behavior and Identity Science, 2023
An essential factor to achieve high performance in face recognition systems is the quality of its samples. Since these systems are involved in 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 of pixels in a face image for recognition. We propose a training-free approach to assess the pixel-level qualities of a face image given an arbitrary face recognition network. To achieve this, a model-specific quality value of the input image is estimated and used to build a sample-specific quality regression model. Based on this model, quality-based gradients are back-propagated and converted into pixel-level quality estimates. In the experiments, we qualitatively and quantitatively investigated the meaningfulness of our proposed pixel-level qualities based on real and artificial disturbances and by comparing the explanation maps on faces incompliant with the ICAO standards. In all scenarios, the results demonstrate that the proposed solution produces meaningful pixel-level qualities enhancing the interpretability of the complete face image quality. The code is publicly available
Uncertainty-aware Comparison Scores for Face Recognition
Marco Huber, Philipp Terhörst, Florian Kirchbuchner, Arjan Kuijper, Naser Damer
2023 11th International Workshop on Biometrics and Forensics Iwbf 2023, 2023
Estimating and understanding uncertainty in face recognition systems is receiving increasing attention as face recognition systems spread worldwide and process privacy and security-related data. In this work, we investigate how such uncertainties can be further utilized to increase the accuracy and therefore the trust of automatic face recognition systems. We propose to use the uncertainties of extracted face features to compute a new uncertainty-aware comparison score (UACS). This score takes into account the estimated uncertainty during the calculation of the comparison score, leading to a reduction in verification errors. To achieve this, we model the comparison score and its uncertainty as a probability distribution and measure its distance to a distribution of an ideal genuine comparison. In extended experiments with three face recognition models and on six benchmarks, we investigated the impact of our approach and demonstrated its benefits in enhancing the verification performance and the genuine-imposter comparison scores separability.
QMagFace: Simple and Accurate Quality-Aware Face Recognition
Philipp Terhorst, Malte Ihlefeld, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper
Proceedings 2023 IEEE Winter Conference on Applications of Computer Vision Wacv 2023, 2023
In this work, we propose QMagFace, a simple and effective face recognition solution (QMagFace) that combines a quality-aware comparison score with a recognition model based on a magnitude-aware angular margin loss. The proposed approach includes model-specific face image qualities in the comparison process to enhance the recognition performance under unconstrained circumstances. Exploiting the linearity between the qualities and their comparison scores induced by the utilized loss, our quality-aware comparison function is simple and highly generalizable. The experiments conducted on several face recognition databases and benchmarks demonstrate that the introduced quality-awareness leads to consistent improvements in the recognition performance. Moreover, the proposed QMagFace approach performs especially well under challenging circumstances, such as cross-pose, cross-age, or cross-quality. Consequently, it leads to state-of-the-art performances on several face recognition benchmarks, such as 98.50% on AgeDB, 83.95% on XQLFQ, and 98.74% on CFP-FP. The code for QMagFace is publicly available1.
Masked face recognition: Human versus machine
Naser Damer, Fadi Boutros, Marius Süßmilch, Meiling Fang, Florian Kirchbuchner, Arjan Kuijper
Iet Biometrics, 2022
Abstract 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. Recent reports have tackled this by evaluating the masked probe effect on the performance of automatic FR solutions. However, such solutions can fail in certain processes, leading to the verification task being performed by a human expert. This work provides a joint evaluation and in‐depth analyses of the face verification performance of human experts in comparison to state‐of‐the‐art automatic FR solutions. This involves an extensive evaluation by human experts and 4 automatic recognition solutions. The study concludes with a set of take‐home messages on different aspects of the correlation between the verification behaviour of humans and machines.
Self-restrained triplet loss for accurate masked face recognition
Fadi Boutros, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Pattern Recognition, 2022
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 emerging challenge for face recognition systems. In this paper, we present a solution to improve masked face recognition performance. Specifically, we propose the Embedding Unmasking Model (EUM) operated on top of existing face recognition models. We also propose a novel loss function, the Self-restrained Triplet (SRT), which enabled the EUM to produce embeddings similar to these of unmasked faces of the same identities. The achieved evaluation results on three face recognition models, two real masked datasets, and two synthetically generated masked face datasets proved that our proposed approach significantly improves the performance in most experimental settings.
Lightweight Long Short-Term Memory Variational Auto-Encoder for Multivariate Time Series Anomaly Detection in Industrial Control Systems
Daniel Fährmann, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Sensors, 2022
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. This poses a threat to the infrastructure that is critical for the operation of a modern city. Nowadays, the best techniques for detecting anomalies in ICSs are based on machine learning and, more recently, deep learning. Cybersecurity in ICSs is still an emerging field, and industrial datasets that can be used to develop anomaly detection techniques are rare. In this paper, we propose an unsupervised deep learning methodology for anomaly detection in ICSs, specifically, a lightweight long short-term memory variational auto-encoder (LW-LSTM-VAE) architecture. We successfully demonstrate our solution under two ICS applications, namely, water purification and water distribution plants. Our proposed method proves to be efficient in detecting anomalies in these applications and improves upon reconstruction-based anomaly detection methods presented in previous work. For example, we successfully detected 82.16% of the anomalies in the scenario of the widely used Secure Water Treatment (SWaT) benchmark. The deep learning architecture we propose has the added advantage of being extremely lightweight.
Real masks and spoof faces: On the masked face presentation attack detection
Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Pattern Recognition, 2022
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 studies, the impact of face masked attacks on PAD has not been explored. Therefore, we present novel attacks with real face masks placed on presentations and attacks with subjects wearing masks to reflect the current real-world situation. Furthermore, this study investigates the effect of masked attacks on PAD performance by using seven state-of-the-art PAD algorithms under different experimental settings. We also evaluate the vulnerability of FR systems to masked attacks. The experiments show that real masked attacks pose a serious threat to the operation and security of FR systems.
Template-Driven Knowledge Distillation for Compact and Accurate Periocular Biometrics Deep-Learning Models
Fadi Boutros, Naser Damer, Kiran Raja, Florian Kirchbuchner, Arjan Kuijper
Sensors, 2022
A Comprehensive Study on Face Recognition Biases beyond Demographics
Philipp Terhorst, Jan Niklas Kolf, Marco Huber, Florian Kirchbuchner, Naser Damer, Aythami Morales Moreno, Julian Fierrez, Arjan Kuijper
IEEE Transactions on Technology and Society, 2022
Acquisition of EFS and Capacitive Measurement Data on Low-Power and Connected IoT Devices
Julian von Wilmsdorff, Malte Lenhart, Florian Kirchbuchner, Arjan Kuijper
Communications in Computer and Information Science, 2022
Learnable Multi-level Frequency Decomposition and Hierarchical Attention Mechanism for Generalized Face Presentation Attack Detection
Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Proceedings 2022 IEEE Cvf Winter Conference on Applications of Computer Vision Wacv 2022, 2022
Lightweight Periocular Recognition through Low-bit Quantization
Jan Niklas Kolf, Fadi Boutros, Florian Kirchbuchner, Naser Damer
2022 IEEE International Joint Conference on Biometrics Ijcb 2022, 2022
ElasticFace: Elastic Margin Loss for Deep Face Recognition
F. Boutros, N. Damer, Florian Kirchbuchner, Arjan Kuijper
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2022
Verification of Sitter Identity Across Historical Portrait Paintings by Confidence-aware Face Recognition
Marco Huber, Philipp Terhorst, Anh Thi Luu, Florian Kirchbuchner, Naser Damer
Proceedings International Conference on Pattern Recognition, 2022
The overlapping effect and fusion protocols of data augmentation techniques in iris PAD
Meiling Fang, Naser Damer, Fadi Boutros, Florian Kirchbuchner, Arjan Kuijper
Machine Vision and Applications, 2022
Stating Comparison Score Uncertainty and Verification Decision Confidence Towards Transparent Face Recognition
Bmvc 2022 33rd British Machine Vision Conference Proceedings, 2022
On Evaluating Pixel-Level Face Image Quality Assessment
European Signal Processing Conference, 2022
Double Deep Q-Learning With Prioritized Experience Replay for Anomaly Detection in Smart Environments
Daniel Fahrmann, Nils Jorek, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
IEEE Access, 2022
PocketNet: Extreme Lightweight Face Recognition Network Using Neural Architecture Search and Multistep Knowledge Distillation
Fadi Boutros, Patrick Siebke, Marcel Klemt, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
IEEE Access, 2022
Low-resolution Iris Recognition via Knowledge Transfer
Fadi Boutros, Olga Kaehm, Meiling Fang, Florian Kirchbuchner, Naser Damer, Arjan Kuijper
Biosig 2022 Proceedings of the 21st International Conference of the Biometrics Special Interest Group, 2022
On the (Limited) Generalization of MasterFace Attacks and Its Relation to the Capacity of Face Representations
Philipp Terhorst, Florian Bierbaum, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper
2022 IEEE International Joint Conference on Biometrics Ijcb 2022, 2022
On Soft-Biometric Information Stored in Biometric Face Embeddings
Philipp Terhorst, Daniel Fahrmann, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
IEEE Transactions on Biometrics Behavior and Identity Science, 2021
Extended evaluation of the effect of real and simulated masks on face recognition performance
Naser Damer, Fadi Boutros, Marius Süßmilch, Florian Kirchbuchner, Arjan Kuijper
Iet Biometrics, 2021
Iris Presentation Attack Detection by Attention-based and Deep Pixel-wise Binary Supervision Network
Meiling Fang, Naser Damer, Fadi Boutros, Florian Kirchbuchner, Arjan Kuijper
2021 IEEE International Joint Conference on Biometrics Ijcb 2021, 2021
Midecon: Unsupervised and accurate fingerprint and minutia quality assessment based on minutia detection confidence
Philipp Terhorst, Andre Boller, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
2021 IEEE International Joint Conference on Biometrics Ijcb 2021, 2021
Mixfacenets: Extremely efficient face recognition networks
Fadi Boutros, Naser Damer, Meiling Fang, Florian Kirchbuchner, Arjan Kuijper
2021 IEEE International Joint Conference on Biometrics Ijcb 2021, 2021
MFR 2021: Masked Face Recognition Competition
Fadi Boutros, Naser Damer, Jan Niklas Kolf, Kiran Raja, Florian Kirchbuchner, Raghavendra Ramachandra, Arjan Kuijper, Pengcheng Fang, Chao Zhang, Fei Wang, David Montero, Naiara Aginako, Basilio Sierra, Marcos Nieto, Mustafa Ekrem Erakin, Ugur Demir, Hazim Kemal Ekenel, Asaki Kataoka, Kohei Ichikawa, Shizuma Kubo, Jie Zhang, Mingjie He, Dan Han, Shiguang Shan, Klemen Grm, Vitomir Struc, Sachith Seneviratne, Nuran Kasthuriarachchi, Sanka Rasnayaka, Pedro C. Neto, Ana F. Sequeira, Joao Ribeiro Pinto, Mohsen Saffari, Jaime S. Cardoso
2021 IEEE International Joint Conference on Biometrics Ijcb 2021, 2021
Demographic bias in presentation attack detection of iris recognition systems
Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
European Signal Processing Conference, 2021
The Effect of Wearing a Face Mask on Face Image Quality
Biying Fu, Florian Kirchbuchner, Naser Damer
Proceedings 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition Fg 2021, 2021
Mask-invariant Face Recognition through Template-level Knowledge Distillation
Marco Huber, Fadi Boutros, Florian Kirchbuchner, Naser Damer
Proceedings 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition Fg 2021, 2021
Linoc: A prototyping platform for capacitive and passive electrical field sensing
Sensornets 2021 Proceedings of the 10th International Conference on Sensor Networks, 2021
Generalization of Fitness Exercise Recognition from Doppler Measurements by Domain-Adaption and Few-Shot Learning
Biying Fu, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Lecture Notes in Computer Science, 2021
Cross-database and cross-attack Iris presentation attack detection using micro stripes analyses
Meiling Fang, Naser Damer, Fadi Boutros, Florian Kirchbuchner, Arjan Kuijper
Image and Vision Computing, 2021
PW-MAD: Pixel-Wise Supervision for Generalized Face Morphing Attack Detection
Naser Damer, Noémie Spiller, Meiling Fang, Fadi Boutros, Florian Kirchbuchner, Arjan Kuijper
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2021
MAAD-Face: A Massively Annotated Attribute Dataset for Face Images
Philipp Terhorst, Daniel Fahrmann, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
IEEE Transactions on Information Forensics and Security, 2021
ReGenMorph: Visibly Realistic GAN Generated Face Morphing Attacks by Attack Re-generation
Naser Damer, Kiran Raja, Marius Süßmilch, Sushma Venkatesh, Fadi Boutros, Meiling Fang, Florian Kirchbuchner, Raghavendra Ramachandra, Arjan Kuijper
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2021
Performing Realistic Workout Activity Recognition on Consumer Smartphones
Biying Fu, Florian Kirchbuchner, Arjan Kuijper
Technologies, 2020
Post-comparison mitigation of demographic bias in face recognition using fair score normalization
Philipp Terhörst, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Pattern Recognition Letters, 2020
Iris and periocular biometrics for head mounted displays: Segmentation, recognition, and synthetic data generation
Fadi Boutros, Naser Damer, Kiran Raja, Raghavendra Ramachandra, Florian Kirchbuchner, Arjan Kuijper
Image and Vision Computing, 2020
Assessing users' privacy and security concerns of smart home technologies
Verena Zimmermann, Paul Gerber, Karola Marky, Leon Böck, Florian Kirchbuchner
I Com, 2020
Micro stripes analyses for iris presentation attack detection
Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Ijcb 2020 IEEE Iapr International Joint Conference on Biometrics, 2020
Beyond identity: What information is stored in biometric face templates?
Philipp Terhorst, Daniel Fahrmann, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Ijcb 2020 IEEE Iapr International Joint Conference on Biometrics, 2020
Face quality estimation and its correlation to demographic and non-demographic bias in face recognition
Philipp Terhorst, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Ijcb 2020 IEEE Iapr International Joint Conference on Biometrics, 2020
On benchmarking iris recognition within a head-mounted display for AR/VR applications
Fadi Boutros, Naser Damer, Kiran Raja, Raghavendra Ramachandra, Florian Kirchbuchner, Arjan Kuijper
Ijcb 2020 IEEE Iapr International Joint Conference on Biometrics, 2020
Compact Models for Periocular Verification through Knowledge Distillation
Biosig 2020 Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020
The Effect of Wearing a Mask on Face Recognition Performance: An Exploratory Study
Biosig 2020 Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020
Face Presentation Attack Detection in Ultraviolet Spectrum via Local and Global Features
Biosig 2020 Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020
Privacy Evaluation Protocols for the Evaluation of Soft-Biometric Privacy-Enhancing Technologies
Biosig 2020 Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020
Deep learning multi-layer fusion for an accurate iris presentation attack detection
Meiling Fang, Naser Damer, Fadi Boutros, Florian Kirchbuchner, Arjan Kuijper
Proceedings of 2020 23rd International Conference on Information Fusion Fusion 2020, 2020
Fusing iris and periocular region for user verification in head mounted displays
Fadi Boutros, Naser Damer, Kiran Raja, Raghavendra Ramachandra, Florian Kirchbuchner, Arjan Kuijper
Proceedings of 2020 23rd International Conference on Information Fusion Fusion 2020, 2020
Data augmentation for time series: Traditional vs generative models on capacitive proximity time series
Biying Fu, Florian Kirchbuchner, Arjan Kuijper
ACM International Conference Proceeding Series, 2020
Unconstrained workout activity recognition on unmodified commercial off-the-shelf smartphones
Biying Fu, Florian Kirchbuchner, Arjan Kuijper
ACM International Conference Proceeding Series, 2020
Designing smart home controls for elderly
Silvia Rus, Stefan Helfmann, Florian Kirchbuchner, Arjan Kuijper
ACM International Conference Proceeding Series, 2020
Comparison-Level Mitigation of Ethnic Bias in Face Recognition
Philipp Terhorst, Mai Ly Tran, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
2020 8th International Workshop on Biometrics and Forensics Iwbf 2020 Proceedings, 2020
Periocular Biometrics in Head-Mounted Displays: A Sample Selection Approach for Better Recognition
Fadi Boutros, Naser Damer, Kiran Raja, Raghavendra Ramachandra, Florian Kirchbuchner, Arjan Kuijper
2020 8th International Workshop on Biometrics and Forensics Iwbf 2020 Proceedings, 2020
ExerTrack—Towards Smart Surfaces to Track Exercises
Biying Fu, Lennart Jarms, Florian Kirchbuchner, Arjan Kuijper
Technologies, 2020
Sensing technology for human activity recognition: A comprehensive survey
Biying Fu, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
IEEE Access, 2020
SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding Robustness
Philipp Terhorst, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2020
The Effect of Wearing a Mask on Face Recognition Performance: an Exploratory Study
Lecture Notes in Informatics Lni Proceedings Series of the Gesellschaft Fur Informatik Gi, 2020
Compact Models for Periocular Verification Through Knowledge Distillation
Lecture Notes in Informatics Lni Proceedings Series of the Gesellschaft Fur Informatik Gi, 2020
Face Presentation Attack Detection in Ultraviolet Spectrum via Local and Global Features
Lecture Notes in Informatics Lni Proceedings Series of the Gesellschaft Fur Informatik Gi, 2020
Privacy Evaluation Protocols for the Evaluation of Soft-Biometric Privacy-Enhancing Technologies
Lecture Notes in Informatics Lni Proceedings Series of the Gesellschaft Fur Informatik Gi, 2020
PE-MIU: A Training-Free Privacy-Enhancing Face Recognition Approach Based on Minimum Information Units
Philipp Terhorst, Kevin Riehl, Naser Damer, Peter Rot, Blaz Bortolato, Florian Kirchbuchner, Vitomir Struc, Arjan Kuijper
IEEE Access, 2020
D-ID-net: Two-stage domain and identity learning for identity-preserving image generation from semantic segmentation
Naser Damer, Fadi Boutros, Florian Kirchbuchner, Arjan Kuijper
Proceedings 2019 International Conference on Computer Vision Workshop Iccvw 2019, 2019
Eye-MMS: Miniature multi-scale segmentation network of key eye-regions in embedded applications
Fadi Boutros, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Proceedings 2019 International Conference on Computer Vision Workshop Iccvw 2019, 2019
Realistic Dreams: Cascaded Enhancement of GAN-generated Images with an Example in Face Morphing Attacks
Naser Damer, Fadi Boutros, Alexandra Mosegui Saladie, Florian Kirchbuchner, Arjan Kuijper
2019 IEEE 10th International Conference on Biometrics Theory Applications and Systems Btas 2019, 2019
On the Generalization of Detecting Face Morphing Attacks as Anomalies: Novelty vs. Outlier Detection
Naser Damer, Jonas Henry Grebe, Steffen Zienert, Florian Kirchbuchner, Arjan Kuijper
2019 IEEE 10th International Conference on Biometrics Theory Applications and Systems Btas 2019, 2019
Reliable Age and Gender Estimation from Face Images: Stating the Confidence of Model Predictions
Philipp Terhorst, Marco Huber, Jan Niklas Kolf, Ines Zelch, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
2019 IEEE 10th International Conference on Biometrics Theory Applications and Systems Btas 2019, 2019
Unsupervised privacy-enhancement of face representations using similarity-sensitive noise transformations
Philipp Terhörst, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
Applied Intelligence, 2019
Exploring the Channels of Multiple Color Spaces for Age and Gender Estimation from Face Images
Fusion 2019 22nd International Conference on Information Fusion, 2019
A Multi-detector Solution Towards an Accurate and Generalized Detection of Face Morphing Attacks
Fusion 2019 22nd International Conference on Information Fusion, 2019
Multi-algorithmic Fusion for Reliable Age and Gender Estimation from Face Images
Fusion 2019 22nd International Conference on Information Fusion, 2019
Designing a self-aware jacket: Insights into Smart Garment's creation process
Silvia Rus, Andreas Braun, Florian Kirchbuchner, Arjan Kuijper
ACM International Conference Proceeding Series, 2019
E-textile capacitive electrodes: Fabric or thread: Designing an e-textile cushion for sitting posture detection
Silvia Rus, Andreas Braun, Florian Kirchbuchner, Arjan Kuijper
ACM International Conference Proceeding Series, 2019
Suppressing Gender and Age in Face Templates Using Incremental Variable Elimination
Philipp Terhörst, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
2019 International Conference on Biometrics Icb 2019, 2019
To Detect or not to Detect: The Right Faces to Morph
Naser Damer, Alexandra Moseguí Saladié, Steffen Zienert, Yaza Wainakh, Philipp Terhörst, et al.
2019 International Conference on Biometrics Icb 2019, 2019
An experimental overview on electric field sensing
Julian von Wilmsdorff, Florian Kirchbuchner, Biying Fu, Andreas Braun, Arjan Kuijper
Journal of Ambient Intelligence and Humanized Computing, 2019
Performing indoor localization with electric potential sensing
Biying Fu, Florian Kirchbuchner, Julian von Wilmsdorff, Tobias Grosse-Puppendahl, Andreas Braun, et al.
Journal of Ambient Intelligence and Humanized Computing, 2019
Piggybacking Detection Based on Coupled Body-Feet Recognition at Entrance Control
Dirk Siegmund, Vinh Phuc Tran, Julian von Wilmsdorff, Florian Kirchbuchner, Arjan Kuijper
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2019
On the detection of GAN-based face morphs using established morph detectors
Luca Debiasi, Naser Damer, Alexandra Moseguí Saladié, Christian Rathgeb, Ulrich Scherhag, et al.
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2019
SurfaceVox - Exploring Sound Control for Gesture-Tracking Interactive Surfaces
Andreas Braun, Martin Majewski, Joachim Loge, Florian Kirchbuchner, Arjan Kuijper
Proceedings 14th International Conference on Signal Image Technology and Internet Based Systems Sitis 2018, 2018
Fitness activity recognition on smartphones using doppler measurements
Biying Fu, Florian Kirchbuchner, Arjan Kuijper, Andreas Braun, Dinesh Vaithyalingam Gangatharan
Informatics, 2018
An integrated deep neural network for defect detection in dynamic textile textures
Dirk Siegmund, Ashok Prajapati, Florian Kirchbuchner, Arjan Kuijper
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
Eliminating the ground reference for wireless electric field sensing
Julian von Wilmsdorff, Florian Kirchbuchner, Andreas Braun, Arjan Kuijper
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
Surface acoustic arrays to analyze human activities in smart environments
Biying Fu, Matthias Ruben Mettel, Florian Kirchbuchner, Andreas Braun, Arjan Kuijper
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
Step by step: Early detection of diseases using an intelligent floor
Lisa Scherf, Florian Kirchbuchner, Julian von Wilmsdorff, Biying Fu, Andreas Braun, et al.
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
Prototyping shape-sensing fabrics through physical simulation
Silvia Rus, Felix Hammacher, Julian von Wilmsdorff, Andreas Braun, Tobias Grosse-Puppendahl, et al.
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
Exercise monitoring on consumer smart phones using ultrasonic sensing
Biying Fu, Dinesh Vaithyalingam Gangatharan, Arjan Kuijper, Florian Kirchbuchner, Andreas Braun
ACM International Conference Proceeding Series, 2017
An exploratory study on electric field sensing
Julian von Wilmsdorff, Florian Kirchbuchner, Biying Fu, Andreas Braun, Arjan Kuijper
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2017
Indoor localization based on passive electric field sensing
Biying Fu, Florian Kirchbuchner, Julian von Wilmsdorff, Tobias Grosse-Puppendahl, Andreas Braun, et al.
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2017
Ambient intelligence from senior citizens’ perspectives: Understanding privacy concerns, technology acceptance, and expectations
Florian Kirchbuchner, Tobias Grosse-Puppendahl, Matthias R. Hastall, Martin Distler, Arjan Kuijper
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2015

Florian Kirchbuchner

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