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P296 - BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group

https://dl.gi.de/handle/20.500.12116/34220
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Auflistung P296 - BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group nach Erscheinungsdatum

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  • Konferenzbeitrag
    Anomalies in measuring speed and other dynamic properties with touchscreens and tablets
    (BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Griechisch, Erika; Ward, Jean Renard; Hanczár, Gergely
    Touchscreens and tablets are often used in different studies and applications to capture high-resolution drawing, handwriting, or signatures. Several studies tend to analyse different properties, such as peaks or changes of the time derivatives of the coordinates; like velocity, angular velocity, acceleration or jerk of the movements. These are substantial features to analyse drawing, analyse or recognize handwriting, to examine the fluency of handwriting or verify signatures. The reliability of such a study strongly depends on the fidelity of the acquired data. We have tested several touchscreens and tablets which are widely used in different research studies, focusing on the resolution and accuracy of the coordinates and the uniformity of sampling. We have found that the vendors’ performance specifications (to the extent the vendor gives meaningful specifications) may seriously deviate from reality. Even if some of the raw data may look satisfactory at first sight, our examination uncovered several potentially significant bad behaviors, and instances in which the specifications from the vendors are, at best, misleading and incompletely informative. Some authors mention that the reliability of tablet data is unclear [Ha13, Fr05], but researchers may underestimate to what extent it could influence their results. This paper uncovers some aspects of the unreliability of the data and emphasizes the importance of understanding and addressing (or at least, knowing) the revealed problems prior to any analysis.
  • Konferenzbeitrag
    On the Application of Homomorphic Encryption to Face Identification
    (BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Drozdowski, Pawel; Buchmann, Nicolas; Rathgeb, Christian; Margraf, Marian; Busch, Christoph
    The data security and privacy of enrolled subjects is a critical requirement expected from biometric systems. This paper addresses said topic in facial biometric identification. In order to fulfil the properties of unlinkability, irreversibility, and renewability of the templates required for biometric template protection schemes, homomorphic encryption is utilised. In addition to achieving the aforementioned objectives, the use of homomorphic encryption ensures that the biometric performance remains completely unaffected by the template protection scheme. The main contributions of this paper are: It proposes an architecture of a system capable of performing biometric identification in the encrypted domain, as well as provides and evaluates an implementation using two existing homomorphic encryption schemes. Furthermore, it discusses the pertinent technical considerations and challenges in this context.
  • Konferenzbeitrag
    Gender and Kinship by Model-Based Ear Biometrics
    (BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Meng, Di; Nixon, Mark S.; Mahmoodi, Sasan
    Many studies in biometrics have shown how identity can be determined, including by images of ears. In the paper, we show how model an ear and how the gender appears to often be manifest in the ear structures, as is kinship or family relationship. We describe a new model-based approach for viewpoint correction and ear description to enable this analysis. We show that with the new technique having satisfactory basic recognition capability (recognizing individuals with performance similar to state of art), gender can achieve 67.2% and kinship 40.4% rank 1 recognition on ears from subjects with unconstrained pose.
  • Konferenzbeitrag
    Style Your Face Morph and Improve Your Face Morphing Attack Detector
    (BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Seibold, Clemens; Hilsmann, Anna; Eisert, Peter
    A morphed face image is a synthetically created image that looks so similar to the faces of two subjects that both can use it for verification against a biometric verification system. It can be easily created by aligning and blending face images of the two subjects. In this paper, we propose a style transfer based method that improves the quality of morphed face images. It counters the image degeneration during the creation of morphed face images caused by blending. We analyze different state of the art face morphing attack detection systems regarding their performance against our improved morphed face images and other methods that improve the image quality. All detection systems perform significantly worse, when first confronted with our improved morphed face images. Most of them can be enhanced by adding our quality improved morphs to the training data, which further improves the robustness against other means of quality improvement.
  • Konferenzbeitrag
    Deep Domain Adaption for Convolutional Neural Network (CNN) based Iris Segmentation: Solutions and Pitfalls
    (BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Jalilian, Ehsaneddin; Uhl, Andreas
    Addressing the lack of massive amounts of labeled training data, deep domain adaptation has been applied successfully in many applications of machine learning. We investigate the application of deep domain adaptation for CNN based iris segmentation, exploring available solutions and their corresponding strengths and pitfalls, with several major contributions. First, we provide a comprehensive survey of current deep domain adaptation methods according to the properties of data that cause the domains divergence. Second, after selecting credible methods, we evaluate their expedience in terms of iris segmentation performance. Third, we analyze and compare the performance against the state-of-the-art methods under these categories. Forth, potential shortfalls of current methods and several future directions are pointed out and discussed.
  • Konferenzbeitrag
    Multi-resolution Local Descriptor for 3D Ear Recognition
    (BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Ganapathi, Iyyakutti Iyappan; Ali, Syed Sadaf; Prakash, Surya
    Several approaches have shown promising results in human ear recognition. However, factors such as the pose, illumination, and scaling have an enormous impact on recognition performance. 3D models are insensitive to these factors and are found to be better at enhancing recognition performance with strong geometric information. Low cost 3D data acquisition has also boosted the research community in recent times to explore more about 3D object recognition. We present a local multi-resolution descriptor in this paper to recognize human ears in 3D. For each key-point in 3D ear, a local reference frame (LRF) is constructed. Using multi-radii, we find neighbors at each key-point and the neighbors obtained from each radius are projected to create a depth image using the LRF. Further, a descriptor is computed by employing neural network based auto-encoders and the local statistics of the depth images. The descriptor is used to locate the potential correspondence matching points in the probe and gallery images for a coarse arrangement, followed by a fine alignment to compute the registration error. The obtained registration error is used as the matching score. The proposed technique is assessed on UND-J2 dataset to demonstrate its effectiveness.
  • Konferenzbeitrag
    Region-Based CNNs for Pedestrian Gender Recognition in Visual Surveillance Environments
    (BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Yaghoubi, Ehsan; Alirezazadeh, Pendar; Assunção, Eduardo; Neves, João C.; Proença, Hugo
    Inferring soft biometric labels in totally uncontrolled outdoor environments, such as surveillance scenarios, remains a challenge due to the low resolution of data and its covariates that might seriously compromise performance (e.g., occlusions and subjects pose). In this kind of data, even state-of-the-art deep-learning frameworks (such as ResNet) working in a holistic way, attain relatively poor performance, which was the main motivation for the work described in this paper. In particular, having noticed the main effect of the subjects’ “pose” factor, in this paper we describe a method that uses the body keypoints to estimate the subjects pose and define a set of regions of interest (e.g., head, torso, and legs). This information is used to learn appropriate classification models, specialized in different poses/body parts, which contributes to solid improvements in performance. This conclusion is supported by the experiments we conducted in multiple real-world outdoor scenarios, using the data acquired from advertising panels placed in crowded urban environments.
  • Konferenzbeitrag
    Public Perceptions, Preferences and Legal Aspects towards ATMs with Biometric Authentication in Austria
    (BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Hochwarter, Christoph; Jahnel, Dietmar; Uhl, Andreas
    This article presents the results of a research project designed to investigate (1) the general attitudes and acceptance of the Austrian public towards biometrics in general, (2) towards ATMs with biometric authentication technology, (3) the kind of biometry they prefer for this kind of application, (4) motivational factors and hindrances concerning a potential roll-out of biometric ATMs in Austria and (5) gives legal background information regarding the employment of biometrics in ATMs and the processing of the biometric data. The data used as a basis was provided by a quantitative online survey (n=706). Results indicate that while a (large) minority is opposed to the concept of ATMs with biometrics (28%), an even larger share was positively inclined towards the concept. However, there was no strong preference for a single biometrical approach towards ATMs in the Austrian populace.
  • Konferenzbeitrag
    Multi-algorithm Benchmark for Fingerprint Presentation Attack Detection with Laser Speckle Contrast Imaging
    (BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Kolberg, Jascha; Gomez-Barrero, Marta; Busch, Christoph
    The increased usage of biometric authentication systems has raised concerns regarding the security of components in a biometric system. As a consequence, preventing security issues related to presentation attacks targeting the biometric capture device are of utmost importance. To develop presentation attack detection (PAD) mechanisms, features confirming the liveness of the biometric characteristic such as the blood flow within the finger are needed. Utilising laser speckle contrast imaging (LSCI) to observe blood movement below the surface, we present an evaluation of different machine learning classifiers for fingerprint PAD. The experiments over a database comprising 35 different presentation attack instrument (PAI) species show that the detection performance varies depending on the utilised feature extraction method. A majority voting of selected classifiers and features achieves an APCER of 9% for a convenient BPCER of 0.05%.
  • Konferenzbeitrag
    Android Pattern Unlock Authentication - effectiveness of local and global dynamic features
    (BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Ibrahim, Nasiru; Sellahewa, Harin
    This study conducts a holistic analysis of the performances of biometric features incorporated into Pattern Unlock authentication. The objective is to enhance the strength of the authentication by adding an implicit layer. Earlier studies have incorporated either global or local dynamic features for verification; however, as found in this paper, different features have variable discriminating power, especially at different extraction levels. The discriminating potential of global, local and their combination are evaluated. Results showed that locally extracted features have higher discriminating power than global features and combining both features gives the best verification performance. Further, a novel feature was proposed and evaluated, which was found to have a varied impact (both positive and negative) on the system performance. From our findings, it is essential to evaluate features (independently and collectively), extracted at different levels (global and local) and different combination for some might impede on the verification performance of the system.