Auflistung nach Autor:in "Veldhuis, Raymond"
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- KonferenzbeitragBloom Filter vs Homomorphic Encryption: Which approach protects the biometric data and satisfies ISO/IEC 24745?(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Bassit, Amina; Hahn, Florian; Zeinstra, Chris; Veldhuis, Raymond; Peter, AndreasBloom filter (BF) and homomorphic encryption (HE) are popular modern techniques used to design biometric template protection (BTP) schemes that aim to protect the sensitive biometric information during storage and the comparison process. However, in practice, many BTP schemes based on BF or HE violate at least one of the privacy requirements of the international standard ISO/IEC 24745: irreversibility, unlinkability and confidentiality. In this paper, we investigate the state-of-the-art BTP schemes based on these two approaches and assess their relative strengths and weaknesses with respect to the three requirements of ISO/IEC 24745. The results of our investigation showed that the choice between BF and HE depends on the setting where the BTP scheme will be deployed and the level of trustworthiness of the parties involved in processing the protected template. As a result, HE enhanced by verifiable computation techniques can satisfy the privacy requirements of ISO/IEC 24745 in a trustless setting.
- KonferenzbeitragDesigning a low-resolution face recognition system for long-range surveillance(Biosig 2016, 2016) Peng, Yuxi; Spreeuwers, Luuk; Veldhuis, Raymond
- KonferenzbeitragDiscriminating power of FISWG characteristic descriptors under different forensic use case(Biosig 2016, 2016) Zeinstra, Chris; Veldhuis, Raymond; Sreeuwers, Luuk
- KonferenzbeitragExploring how user routine affects the recognition performance of a lock pattern(BIOSIG 2015, 2015) Wilde, Lisa De; Spreeuwers, Luuk; Veldhuis, RaymondTo protect an Android smartphone against attackers, a lock pattern can be used. Nevertheless, shoulder-surfing and smudge attacks can be used to get access despite of this protection. To combat these attacks, biometric recognition can be added to the lock pattern, such that the lock-pattern application keeps track of the way users draw the pattern. This research explores how users change the way they draw lock patterns over time and its effect on the recognition performance of the pattern. A lock-pattern dataset has been collected and a classifier is proposed. In this research the best result was obtained using the x- and y-coordinate as the user's biometrics. Unfortunately, in this paper it is shown that adding biometrics to a lock pattern is only an additional security that provides no guarantee for a secure lock pattern. It is just a small improvement over using a lock pattern without biometric identification.
- KonferenzbeitragFEERCI: A Package for Fast Non-Parametric Confidence Intervals for Equal Error Rates in Amortized O(m log n)(BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group, 2018) Haasnoot, Erwin; Khodabakhsh, Ali; Zeinstra, Chris; Spreeuwers, Luuk; Veldhuis, RaymondEqual Error Rates (EERs), or other weighted relations between False Match and Non- Match Rates (FMR/FNMR), are often used as a performance metric for biometric systems. Confidence Intervals (CIs) are used to denote the uncertainty underlying these EERs, with many methods existing to estimate said CIs in both parametric and non-parametric ways. These confidence intervals provide, foremost, a method of comparing scoring/ranking functions. Non-parametric methods often suffer from high computational costs, but do not make assumptions as to the shape of the EERand score distributions. For both EERs and CIs, contemporary open-source toolkits leave room for improvement in terms of computational efficiency. In this paper, we introduce the Fast EER (FEER) algorithm that calculates an EER in O(logn) on a sorted score list, we show how to adapt the FEER algorithm to calculate non-parametric, bootstrapped EER CIs (FEERCI) in O(mlogn) given m resamplings, and we introduce an opinionated open-source package named feerci that provides implementations of the FEER and FEERCI algorithm.We provide speed and accuracy benchmarks for the feerci package, comparing it against the most-used methods of calculating EERs in Python and show how it is able to calculate EERs and CIs on very large score lists faster than contemporary toolkits can calculate a single EER.
- KonferenzbeitragForensic biometrics: from two communities to one discipline(BIOSIG 2012, 2012) Meuwly, Didier; Veldhuis, RaymondThis article describes how the fields of biometrics and forensic science can contribute and benefit from each other. The aim is to foster the development of new methods and tools improving the current forensic biometric applications and allowing for the creation of new ones. The article begins with a definition and a summary of the development in forensic biometrics. Then it describes the data and biometric modalities of interest in forensic science and the forensic applications embedding biometric technology. On this basis it describes the solutions and limitations of the current practice regarding the data, the technology and the inference models. Finally, it proposes research orientations for the improvement of the current forensic biometric applications and suggests some ideas for the development of some new forensic biometric applications
- KonferenzbeitragLandmark-based model-free 3D face shape reconstruction from video sequences(BIOSIG 2013, 2013) Dam, Chris van; Veldhuis, Raymond; Spreeuwers, LuukIn forensic comparison of facial video data, often only the best quality frontal face frames are selected, and hence potentially useful video data is ignored. To improve 2D facial comparison for law enforcement and forensic investigation, we introduce a model-free 3D shape reconstruction algorithm based on 2D landmarks. The algorithm uses around 20 landmarks on the face and combines the structure information of multiple frames. Model based 3D reconstruction methods, such as Morphable Models, reconstruct a 3D face shape model that is strongly biased towards the average face. Therefore, we don't use statistical face shape models in our model-free approach. The 3D landmark reconstruction algorithm simultaneously estimates the shape, pose and position of the face, based only on the fact that all images in the sequence are recorded using a single calibrated camera. The algorithm iteratively updates the reconstruction by including new frames, while maintaining the consistency of the reconstruction. We demonstrate the convergence properties of the method reflected in the 2D reprojection error and the 3D error with respect to a ground truth model. We show that the quality of the reconstruction depends on the level of noise in the landmarks. In follow-up experiments we show that our method is able to reconstruct the 3D structure of a face, using a styrofoam head and real video data. The results of the real face data show the same behavior as the results of the simulated data, which indicates that our method is capable of reconstructing real facial structures, depending on the noise of the landmarks.
- KonferenzbeitragOptimal Decision Fusion and Its Application on 3D Face Recognition(BIOSIG 2007: biometrics and electronic signatures, 2007) Tao, Qian; Rootseler, Robin van; Veldhuis, Raymond; Gehlen, Stefan; Weber, FrankFusion is a popular practice to combine multiple classifiers or multiple modalities in biometrics. In this paper, optimal decision fusion (ODF) by AND rule and OR rule is presented. We show that the decision fusion can be done in an optimal way such that it always gives an improvement in terms of error rates over the classifiers that are fused. Both the optimal decision fusion theory and the experimental results on the FRGC 2D and 3D face data are given. Experiments show that the optimal decision fusion effectively combines the 2D texture and 3D shape information, and boosts the performance of the system.