P306 - BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group
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Auflistung P306 - BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group nach Autor:in "Brömme, Arslan"
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- Konferenzbeitrag3D Face Recognition For Cows(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Yeleshetty, Deepak; Spreeuwers, Luuk; Li, YanThis paper presents a method to recognize cows using their 3D face point clouds. Face is chosen because of the rigid structure of the skull compared to other parts. The 3D face point clouds are acquired using a newly designed dual 3D camera setup. After registering the 3D faces to a specific pose, the cow’s ID is determined by running Iterative Closest Point (ICP) method on the probe against all the point clouds in the gallery. The root mean square error (RMSE) between the ICP correspondences is used to identify the cows. The smaller the RMSE, the more likely that the cow is from the same class. In a closed set of 32 cows with 5 point clouds per cow in the gallery, the ICP recognition demonstrates an almost perfect identification rate of 99.53%.
- KonferenzbeitragAction-Independent Generalized Behavioral Identity Descriptors for Look-alike Recognition in Videos(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Khodabakhsh, Ali; Loiselle, HugoThere is a long history of exploitation of the visual similarity of look-alikes for fraud and deception. The visual similarity along with the application of physical and digital cosmetics greatly challenges the recognition ability of average humans. Face recognition systems are not an exception in this regard and are vulnerable to such similarities. In contrast to physiological face recognition, behavioral face recognition is often overlooked due to the outstanding success of the former. However, the behavior of a person can provide an additional source of discriminative information with regards to the identity of individuals when physiological attributes are not reliable. In this study, we propose a novel biometric recognition system based only on facial behavior for the differentiation of look-alikes in unconstrained recording conditions. To this end, we organized a dataset of 85;656 utterances from 1000 look-alike pairs based on videos collected from the wild, large enough for the development of deep learning solutions. Our selection criteria assert that for these collected videos, both state-of-the-art biometric systems and human judgment fail in recognition. Furthermore, to utilize the advantage of large-scale data, we introduce a novel action-independent biometric recognition system that was trained using triplet-loss to create generalized behavioral identity embeddings. We achieve look-alike recognition equal-error-rate of 7:93% with sole reliance on the behavior descriptors extracted from facial landmark movements. The proposed method can have applications in face recognition as well as presentation attack detection and Deepfake detection.
- KonferenzbeitragApplication of affine-based reconstruction to retinal point patterns(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Sadeghpour, Mahshid; Arakala, Arathi; Davis, Stephen A.; Horadam, Kathy J.Inverse biometrics that exploit the information of biometric references from comparison scores can compromise sensitive personal information of the users in biometric recognition systems. One inverse biometric method that has been very successful in regenerating face images applies an affine transformation to model the face recognition algorithm. This method is general and could apply to templates extracted from other biometric characteristics. This research proposes two formats to apply this method to spatial point patterns extracted from retina images and tests its performance on reconstructing such sparse templates. The results show that the quality of the reconstructed retina point pattern templates is lower than would be accepted by the system as mated.
- KonferenzbeitragBiometric System for Mobile Validation of ID And Travel Documents(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Medvedev, V; Gonçalves, Nuno; Cruz, LeandroCurrent trends in security of ID and travel documents require portable and efficient validation applications that rely on biometric recognition. Such tools can allow any authority and citizen to validate documents and authenticate citizens with no need of expensive and sometimes unavailable proprietary devices. In this work, we present a novel, compact and efficient approach of validating ID and travel documents for offline mobile applications. The approach employs the in-house biometric template that is extracted from the original portrait photo (either full frontal or token frontal), and then stored on the ID document with use of a machine readable code (MRC). The ID document can then be validated with a developed application on a mobile device with digital camera. The similarity score is estimated with use of an artificial neural network (ANN). Results show that we achieve validation accuracy up to 99.5% with corresponding false match rate = 0.0047 and false non-match rate = 0.00034.
- KonferenzbeitragBIOSIG 2020 - Komplettband(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020)
- KonferenzbeitragCan Generative Colourisation Help Face Recognition?(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Drozdowski, Pawel; Fischer, Daniel; Rathgeb, Christian; Geissler, Julian; Knedlik, Jan; Busch, ChristophGenerative colourisation methods can be applied to automatically convert greyscale images to realistically looking colour images. In a face recognition system, such techniques might be employed as a pre-processing step in scenarios where either one or both face images to be compared are only available in greyscale format. In an experimental setup which reflects said scenarios, we investigate if generative colourisation can improve face sample utility and overall biometric performance of face recognition. To this end, subsets of the FERET and FRGCv2 face image databases are converted to greyscale and colourised applying two versions of the DeOldify colourisation algorithm. Face sample quality assessment is done using the FaceQnet quality estimator. Biometric performance measurements are conducted for the widely used ArcFace system with its built-in face detector and reported according to standardised metrics. Obtained results indicate that, for the tested systems, the application of generative colourisation does neither improve face image quality nor recognition performance. However, generative colourisation was found to aid face detection and subsequent feature extraction of the used face recognition system which results in a decrease of the overall false reject rate.
- KonferenzbeitragChildFace: Gender Aware Child Face Aging(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Chandaliya, Praveen Kumar; Sinha, Aditya; Nain, NeetaChild face aging and rejuvenation has amassed considerable active research interest due to its immense impact on monitoring applications especially for finding lost/abducted children with childhood photos and hence protect children. Prior studies are primarily motivated to enhance the generation quality and aging of face images, rather than quantifying face recognition performance. To address this challenge we propose ChildFace model. Our model does child face aging and rejuvenation while using gender as condition. Our model uses Conditional Generative Adversarial Nets (cGANs), VGG19 based perceptual loss and LightCNN29 age classifier and produces impressive results. Intense quantitative study based on verification, identification and age estimation proves that our model is competent to existing state-of-art models and can make a significant contribution in identifying missing children.
- KonferenzbeitragCompact Models for Periocular Verification Through Knowledge Distillation(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Boutros, Fadi; Damer, Naser; Fang, Meiling; Raja, Kiran; Kirchbuchner, Florian; Kuijper, ArjanDespite the wide use of deep neural network for periocular verification, achieving smaller deep learning models with high performance that can be deployed on low computational powered devices remains a challenge. In term of computation cost, we present in this paper a lightweight deep learning model with only 1.1m of trainable parameters, DenseNet-20, based on DenseNet architecture. Further, we present an approach to enhance the verification performance of DenseNet-20 via knowledge distillation. With the experiments on VISPI dataset captured with two different smartphones, iPhone and Nokia, we show that introducing knowledge distillation to DenseNet-20 training phase outperforms the same model trained without knowledge distillation where the Equal Error Rate (EER) reduces from 8.36% to 4.56% EER on iPhone data, from 5.33% to 4.64% EER on Nokia data, and from 20.98% to 15.54% EER on cross-smartphone data.
- KonferenzbeitragDevelopment and empirical optimization of an electrochemical analysis cell for the visualization of latent fingerprints and their chemical adhesives(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Bergmann, Tommy; Gottschall, Sebastian; Fuchs, Enrico; Berlipp, Oliver; Labudde, DirkFingerprint analysis played a major role in the investigation of criminal offences for the past 100 years and is often the sole means of criminal identification [YA04]. Electrochemical analysis can yield important additional evidence like fingerprint age, biological age and gender of its creator as well as chemical adhesives [GRW12]. Additional gained characteristics through electrochemical analysis can supplement latent or incomplete fingerprints. In previous work a ruthenium-complex based solution was used as illuminant. Since luminol is readily available and is used in many forensic applications, the presented paper will focus on luminol as an alternative chemical for the ECL-aided visualization of fingerprints. Experiments were conducted by creating an electrochemical reaction inside a purpose build analysis cell. Eccrine, sebaceous glandlike and vaseline contaminated fingerprints were created on a stainless-steel plate placed inside the cell and investigated while applying direct current. Aim of this research was to investigate which kind of fingerprints can be visualized and which quality of the resulting images can be reached using luminol as illuminant. The used laboratory power supply created a strong light reaction at the start of each experiment revealing potential for further enhancement of the image quality. Eccrine dactyloscopic evidence showed no visible results. For sebaceous glandlike fingerprints age was discovered to significantly influence image quality.
- KonferenzbeitragThe 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) Damer, Naser; Grebe, Jonas Henry; Chen, Cong; Boutros, Fadi; Kirchbuchner, Florian; Kuijper, ArjanFace recognition has become essential in our daily lives as a convenient and contactless method of accurate identity verification. Process such as identity verification at automatic border control gates or the secure login to electronic devices are increasingly dependant on such technologies. The recent COVID-19 pandemic have increased the value of hygienic and contactless identity verification. 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. We address that by presenting a specifically collected database containing three session, each with three different capture instructions, to simulate realistic use cases.We further study the effect of masked face probes on the behaviour of three top-performing face recognition systems, two academic solutions and one commercial off-the-shelf (COTS) system.