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2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)最新文献

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On Detecting GANs and Retouching based Synthetic Alterations 基于合成修饰的gan检测与修饰
2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2018-10-01 DOI: 10.1109/BTAS.2018.8698545
Anubhav Jain, Richa Singh, Mayank Vatsa
{"title":"On Detecting GANs and Retouching based Synthetic Alterations","authors":"Anubhav Jain, Richa Singh, Mayank Vatsa","doi":"10.1109/BTAS.2018.8698545","DOIUrl":"https://doi.org/10.1109/BTAS.2018.8698545","url":null,"abstract":"Digitally retouching images has become a popular trend, with people posting altered images on social media and even magazines posting flawless facial images of celebrities. Further, with advancements in Generative Adversarial Networks (GANs), now changing attributes and retouching have become very easy. Such synthetic alterations have adverse effect on face recognition algorithms. While researchers have proposed to detect image tampering, detecting GANs generated images has still not been explored. This paper proposes a supervised deep learning algorithm using Convolutional Neural Networks (CNNs) to detect synthetically altered images. The algorithm yields an accuracy of 99.65% on detecting retouching on the ND-IIITD dataset. It outperforms the previous state of the art which reported an accuracy of 87% on the database. For distinguishing between real images and images generated using GANs, the proposed algorithm yields an accuracy of 99.83%.","PeriodicalId":409205,"journal":{"name":"2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123350561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 31
Comparison of Deep Learning Models for Biometric-based Mobile User Authentication 基于生物特征的移动用户认证深度学习模型比较
2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2018-10-01 DOI: 10.1109/BTAS.2018.8698586
N. Reddy, A. Rattani, R. Derakhshani
{"title":"Comparison of Deep Learning Models for Biometric-based Mobile User Authentication","authors":"N. Reddy, A. Rattani, R. Derakhshani","doi":"10.1109/BTAS.2018.8698586","DOIUrl":"https://doi.org/10.1109/BTAS.2018.8698586","url":null,"abstract":"Recent advances have demonstrated the efficacy of deep learning models for mobile biometrics. In this paper, we evaluate and compare different deep learning models in terms of their efficiency and accuracy when used for biometric user authentication on mobile devices. To this aim, well-known pre-trained architectures such as VGG, ResNet, DenseNet and models proposed for mobile vision applications such as MobileNetVl, MobileNetV2, and NasNet-mobile, are compared with respect to their matching performance and computational cost. Further, we propose a compact and fast custom deep learning model for efficient operations on resource-constrained mobile devices. Experimental investigations were performed as a case study on mobile ocular biometrics using a large-scale VISOB dataset. Reported results suggest the best trade-off between performance and computational cost by our custom model over existing deep learning architectures.","PeriodicalId":409205,"journal":{"name":"2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115963367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 20
BTAS 2018 Ad Page BTAS 2018广告页
2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2018-10-01 DOI: 10.1109/btas.2018.8698569
{"title":"BTAS 2018 Ad Page","authors":"","doi":"10.1109/btas.2018.8698569","DOIUrl":"https://doi.org/10.1109/btas.2018.8698569","url":null,"abstract":"","PeriodicalId":409205,"journal":{"name":"2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130618777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Near-Infrared Illumination Add-On for Mobile Hand-Vein Acquisition 用于移动手静脉采集的近红外照明附加组件
2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2018-10-01 DOI: 10.1109/BTAS.2018.8698575
L. Debiasi, Christof Kauba, B. Prommegger, A. Uhl
{"title":"Near-Infrared Illumination Add-On for Mobile Hand-Vein Acquisition","authors":"L. Debiasi, Christof Kauba, B. Prommegger, A. Uhl","doi":"10.1109/BTAS.2018.8698575","DOIUrl":"https://doi.org/10.1109/BTAS.2018.8698575","url":null,"abstract":"There is a growing need for mobile authentication solutions. Biometric recognition systems provide several advantages over conventional knowledge and token based solutions. Especially the use of vascular patterns as a biometric trait gains more and more attention. We present a near-infrared illumination add-on for smartphone devices which allows to capture the vascular pattern of the hands (hand-veins). This device is connected and controlled via Bluetooth and customised for the Nexus 5 smartphone but can be easily adopted to fit other models too. Due to the inherent risk of fraudulent authentication attempts on a nontrusted platform like a smartphone, we propose a challenge-response approach to ensure the authenticity of the captured hand-vein images. A hand-vein data set comprising of 31 subjects and 920 images in total is acquired with the presented device. A performance evaluation utilising different hand-vein recognition schemes is conducted to show the applicability of our device and the proposed challenge-response approach.","PeriodicalId":409205,"journal":{"name":"2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125141866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Exploring the Use of IrisCodes for Presentation Attack Detection 探索虹膜码在表示攻击检测中的应用
2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2018-10-01 DOI: 10.1109/BTAS.2018.8698581
Cunjian Chen, A. Ross
{"title":"Exploring the Use of IrisCodes for Presentation Attack Detection","authors":"Cunjian Chen, A. Ross","doi":"10.1109/BTAS.2018.8698581","DOIUrl":"https://doi.org/10.1109/BTAS.2018.8698581","url":null,"abstract":"Iris recognition systems are vulnerable to presentation attacks where an adversary uses artifacts such as cosmetic contact lenses, printed eye images, doll eyes, etc. to undermine the system. In this work, we investigate whether IrisCodes, that are commonly used for iris recognition, can be used for presentation attack detection. IrisCodes are binary phasor features extracted from the geometrically normalized iris, where the annular iris region is transformed to a rectangular entity. We demonstrate that including pupil information in IrisCodes improves presentation attack detection performance. Further, we demonstrate that extracting binary phasor information from the un-normalized iris image-referred to as OcularCode in this paper - can further boost the performance. Experiments involving both printed iris images and cosmetic contact lenses from a benchmark dataset suggest that the proposed methods based on binary phasor codes achieve promising results.","PeriodicalId":409205,"journal":{"name":"2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131349569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Recursive Binary Template Embedding for Face Image Sets 递归二值模板嵌入人脸图像集
2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2018-10-01 DOI: 10.1109/BTAS.2018.8698595
Mengjun Leng, I. Kakadiaris
{"title":"Recursive Binary Template Embedding for Face Image Sets","authors":"Mengjun Leng, I. Kakadiaris","doi":"10.1109/BTAS.2018.8698595","DOIUrl":"https://doi.org/10.1109/BTAS.2018.8698595","url":null,"abstract":"In this paper, we focus on the task of generating compact binary templates for face image sets. Existing set-based templates are extracted from a high-dimensional real-value feature space, and sometimes with complex structure. The process is not very efficient for large-scale applications. Existing binary templates are generated via either a sequence or a tree of projections. The recursive tree structure achieves higher recognition performance, but the number of projections increases exponentially with the binary code length. Thus, we propose a recursive binary embedding algorithm exhibiting an increased recognition power while restricting the number of projections to increase linearly with the code length. Moreover, the proposed embedding can be easily plugged into the modern deep learning architectures for set-based face recognition. Experimental results using the challenge IJB-A dataset illustrate the effectiveness and efficiency of our proposed template for face verification, closed set identification, and open set identification.","PeriodicalId":409205,"journal":{"name":"2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124268212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Hand in Motion: Enhanced Authentication Through Wrist and Mouse Movement 手在运动:增强认证通过手腕和鼠标的运动
2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2018-10-01 DOI: 10.1109/BTAS.2018.8698577
Borui Li, Wen Wang, Yang Gao, V. Phoha, Zhanpeng Jin
{"title":"Hand in Motion: Enhanced Authentication Through Wrist and Mouse Movement","authors":"Borui Li, Wen Wang, Yang Gao, V. Phoha, Zhanpeng Jin","doi":"10.1109/BTAS.2018.8698577","DOIUrl":"https://doi.org/10.1109/BTAS.2018.8698577","url":null,"abstract":"Behavioral biometrics have been long used as a complementary method to the traditional one-time authentication system. Mouse dynamics, representing an individual’s unique patterns of mouse operations, possess a great potential to bridge the security gap between two one-time authentications on the computer. In this paper, we propose a continuous authentication approach by combining the deviceindependent, angle-based mouse movement features and the wrist motion features. Based on a Random Forest Ensemble Classifier (RFEC) and the Sequential Sampling Analysis (SSA), the identity of the user can be continuously verified. Experimental results, based on 26 subjects, show that the proposed approach can reach the False Accept Rate (FAR) of 1.46% and 4.69% for impostors and intruders respectively and a False Reject Rate (FRR) of 0%. Moreover, the proposed approach is proven to be more effective in timely authentication (i.e., making an authentication decision within only 9 to 12 mouse clicks), compared with conventional methods solely based on the mouse geometry and locomotion features.","PeriodicalId":409205,"journal":{"name":"2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122054289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
SSFD: A Face Detector using A Single-scale Feature Map 基于单尺度特征映射的人脸检测器
2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2018-10-01 DOI: 10.1109/BTAS.2018.8698570
Lei Shi, Xiang Xu, I. Kakadiaris
{"title":"SSFD: A Face Detector using A Single-scale Feature Map","authors":"Lei Shi, Xiang Xu, I. Kakadiaris","doi":"10.1109/BTAS.2018.8698570","DOIUrl":"https://doi.org/10.1109/BTAS.2018.8698570","url":null,"abstract":"In this paper, we present a simple but effective face detector (dubbed SSFD), which can localize multi-scale faces. Unlike other multi-scale feature detectors which learn multi-scale features or feature pyramids aggregated from different scale feature maps, SSFD only depends on a single-scale input image and a single-scale feature map to detect faces of various scales. In SSFD, transposed convolutions are leveraged to increase the resolution of feature maps with different strides, which can maintain adequate information for occluded and small faces. In addition, dilated convolutions are deployed to increase the receptive field size, which contributes to obtaining discriminative contextual information. SSFD, which is based on the VGG-16 network, outperforms the ResNet101-based Scale-Face as well as the VGG16-based HR on the WIDER FACE validation dataset.","PeriodicalId":409205,"journal":{"name":"2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134318413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
An Empirical Evaluation of Deep Architectures on Generalization of Smartphone-based Face Image Quality Assessment 基于智能手机的人脸图像质量评估泛化深度架构的经验评价
2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2018-10-01 DOI: 10.1109/BTAS.2018.8698593
P. Wasnik, Raghavendra Ramachandra, K. Raja, C. Busch
{"title":"An Empirical Evaluation of Deep Architectures on Generalization of Smartphone-based Face Image Quality Assessment","authors":"P. Wasnik, Raghavendra Ramachandra, K. Raja, C. Busch","doi":"10.1109/BTAS.2018.8698593","DOIUrl":"https://doi.org/10.1109/BTAS.2018.8698593","url":null,"abstract":"Often biometric authentication relies on the quality of enrolment and probe sample and it is therefore essential to estimate the image quality before a sample is submitted to the enrolment or verification process. The challenges encountered in estimating the quality is due to generalizability over unknown data samples of different origin. To this extent, we try to evaluate various deep learning networks which in theory, show high-performance in generalization. Due to the massive adoption of biometrics in consumer solutions like smartphones, we have chosen Smartphone based Face Recognition Systems (FRS) to carry out our study. The main factors which impact the operating performance of the FRS are illumination, pose, occlusions and facial expressions. Therefore, it is essential to understand and estimate the quality of a facial image accurately. In this paper we present a robust and accurate quality estimating framework using deep neural networks (DNN). This work leverages the benefits of deep learning by transferring the pre-learned features from already trained DNNs such as AlexNet and Inception to estimate the facial image quality. Furthermore, we present the evaluation results for more than 10 techniques and 5 face image databases to analyze the performance generalization, and our results favor the pre-trained DNN models over the hand-crafted methods.","PeriodicalId":409205,"journal":{"name":"2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128582730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
BTAS 2018 Message from the General and Program Chairs 2018年BTAS总主席和项目主席的致辞
2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2018-10-01 DOI: 10.1109/btas.2018.8698543
{"title":"BTAS 2018 Message from the General and Program Chairs","authors":"","doi":"10.1109/btas.2018.8698543","DOIUrl":"https://doi.org/10.1109/btas.2018.8698543","url":null,"abstract":"","PeriodicalId":409205,"journal":{"name":"2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"09 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127229714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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