2020 8th International Workshop on Biometrics and Forensics (IWBF)最新文献_第2页

Analysing a Vein Liveness Detection Scheme 分析一种静脉活动性检测方案

2020 8th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2020-04-01 DOI: 10.1109/IWBF49977.2020.9107960

Thomas Herzog, A. Uhl

引用次数: 7

Ensemble Method for Sexual Predators Identification in Online Chats 在线聊天中识别性侵犯者的集成方法

2020 8th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2020-04-01 DOI: 10.1109/IWBF49977.2020.9107945

M. Fauzi, Patrick A. H. Bours

{"title":"Ensemble Method for Sexual Predators Identification in Online Chats","authors":"M. Fauzi, Patrick A. H. Bours","doi":"10.1109/IWBF49977.2020.9107945","DOIUrl":"https://doi.org/10.1109/IWBF49977.2020.9107945","url":null,"abstract":"Cyber grooming is a compelling problem worldwide nowadays and many reports strongly suggested that it becomes very urgent to tackle this problem to protect the children from sexual exploitation. In this study, we propose an effective method for sexual predator identification in online chats based on two-stage classification. The purpose of the first stage is to distinguish predatory conversations from the normal ones while the second stage aims to tell apart between the predator user and the victim within a single predatory conversation. Finally, some unique predators are derived from the second stage result. We investigate several machine learning classifiers including Naive Bayes, Support Vector Machine, Neural Network, Logistic Regression, Random Forest, K-Nearest Neighbors, and Decision Tree with Bag of Words features using several different term weighting methods for this task. We also proposed two ensemble techniques to improve the classification task. The experiment results on PAN12 dataset show that our best method using soft voting based ensemble for first stage and Naive Bayes based method for the second stage obtained an F0.5-score of 0.9348, which would place as number one in the PAN12 competition ranking.","PeriodicalId":174654,"journal":{"name":"2020 8th International Workshop on Biometrics and Forensics (IWBF)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115138952","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: 17

Contactless Finger Knuckle Authentication under Severe Pose Deformations 严重姿态变形下的非接触式指关节认证

2020 8th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2020-04-01 DOI: 10.1109/IWBF49977.2020.9107951

Ajay Kumar

{"title":"Contactless Finger Knuckle Authentication under Severe Pose Deformations","authors":"Ajay Kumar","doi":"10.1109/IWBF49977.2020.9107951","DOIUrl":"https://doi.org/10.1109/IWBF49977.2020.9107951","url":null,"abstract":"Contactless biometrics identification using finger knuckle images has shown significant potential for the e-business and forensic applications. One of the key challenges in accurately matching the real-world contactless finger knuckle images is related to the knuckle pattern deformations that are involuntarily generated due to finger pose changes. Earlier work in this area therefore acquired fixed pose finger images for the authentication and therefore the performance achieved from such images cannot reflect the expected performance under the deployment scenarios. This paper adopts a new approach to accurately match such finger knuckle images and presents first attempt to authenticate finger-knuckle patterns under severe pose changes. This approach attempts to correct pose related deformations by identifying the correspondence between a fixed number of chosen points between two matched images. The match score is computed using local feature descriptors, at each of these correspondence points, and consolidated to generate average match score. The experimental results are presented in this paper, both using two-session and single-session index finger knuckle images from 221 different subjects, using publicly available database. These results are outperforming and indicate the merit of spatial-domain approach to match deformed finger knuckle images using a fixed number of correspondence points.","PeriodicalId":174654,"journal":{"name":"2020 8th International Workshop on Biometrics and Forensics (IWBF)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132752768","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: 3

Robust video source recognition in presence of motion stabilization 鲁棒视频源识别存在运动稳定

2020 8th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2020-04-01 DOI: 10.1109/IWBF49977.2020.9107957

P. Ferrara, Laurent Beslay

引用次数: 4

Security Assessment of Partially Encrypted Visual Data: Using Iris Recognition as Generic Measure 部分加密视觉数据的安全性评估:利用虹膜识别作为通用测度

2020 8th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2020-04-01 DOI: 10.1109/IWBF49977.2020.9107967

Martin Rieger, Jutta Hämmerle-Uhl, A. Uhl

引用次数: 1

Advanced Multi-Perspective Enrolment in Finger Vein Recognition 手指静脉识别的高级多视角登记

2020 8th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2020-04-01 DOI: 10.1109/IWBF49977.2020.9107968

B. Prommegger, A. Uhl

{"title":"Advanced Multi-Perspective Enrolment in Finger Vein Recognition","authors":"B. Prommegger, A. Uhl","doi":"10.1109/IWBF49977.2020.9107968","DOIUrl":"https://doi.org/10.1109/IWBF49977.2020.9107968","url":null,"abstract":"Finger vein recognition deals with the recognition of subjects based on their venous pattern within the fingers. It has been shown that its recognition accuracy heavily depends on a good alignment of the acquired samples. There are several approaches that try to reduce the impact of finger misplacement. However, none of these approaches is able to prevent all possible types of finger misplacements. As finger vein scanners are evolving towards contact-less acquisition, alignment problems, especially due to longitudinal finger rotation, are becoming even more important. Along with rotation detection and correction, capturing the vein pattern from multiple perspectives, as e.g. in multiple-perspective enrolment (MPE, [1]), is a way to tackle the problem of longitudinal finger rotation. Involving multiple cameras increases cost and complexity of the capturing devices, and therefore their number should be kept to a minimum. Perspective multiplication for MPE (PM-MPE, [2]) successfully reduces the number of cameras needed during enrolment while keeping the recognition rates at a high level. So far, (PM-)MPE has only been applied using Maximum curvature features (MC, [3]). This work analyses further approaches to improve the their recognition rates and investigates the applicability of (PM-)MPE to recognition schemes using features other than MC.","PeriodicalId":174654,"journal":{"name":"2020 8th International Workshop on Biometrics and Forensics (IWBF)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124932730","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: 3

Human Emotion Distribution Learning from Face Images using CNN and LBC Features 基于CNN和LBC特征的人脸图像情感分布学习

2020 8th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2020-04-01 DOI: 10.1109/IWBF49977.2020.9107940

Abeer Almowallad, Victor Sanchez

{"title":"Human Emotion Distribution Learning from Face Images using CNN and LBC Features","authors":"Abeer Almowallad, Victor Sanchez","doi":"10.1109/IWBF49977.2020.9107940","DOIUrl":"https://doi.org/10.1109/IWBF49977.2020.9107940","url":null,"abstract":"Human emotion recognition from facial expressions depicted in images is an active area of research particularly for medical, security and human-computer interaction applications. Since there is no pure emotion, measuring the intensity of several possible emotions depicted in a facial expression image is a challenging task. Previous studies have dealt with this challenge by using label-distribution learning (LDL) and focusing on optimizing a conditional probability function that attempts to reduce the relative entropy of the predicted distribution with respect to the target distribution, which leads to a lack of generality of the model. In this work, we propose a deep learning framework for LDL that uses convolutional neural network (CNN) features to increase the generalization of the trained model. Our framework, which we call EDL-LBCNN, enhances the features extracted by CNNs by incorporating a local binary convolutional (LBC) layer to acquire texture information from the face images. We evaluate our EDL-LBCNN framework on the s-JAFFE dataset. Our experimental results show that the EDL-LBCNN framework can effectively deal with LDL for human emotion recognition and attain a stronger performance than that of state-of-the-art methods.","PeriodicalId":174654,"journal":{"name":"2020 8th International Workshop on Biometrics and Forensics (IWBF)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117240555","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: 3

Interpretable Biometrics: Should We Rethink How Presentation Attack Detection is Evaluated? 可解释生物识别:我们是否应该重新考虑如何评估呈现攻击检测?

2020 8th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2020-04-01 DOI: 10.1109/IWBF49977.2020.9107949

Ana F. Sequeira, W. Silva, João Ribeiro Pinto, Tiago Gonçalves, J. Cardoso

{"title":"Interpretable Biometrics: Should We Rethink How Presentation Attack Detection is Evaluated?","authors":"Ana F. Sequeira, W. Silva, João Ribeiro Pinto, Tiago Gonçalves, J. Cardoso","doi":"10.1109/IWBF49977.2020.9107949","DOIUrl":"https://doi.org/10.1109/IWBF49977.2020.9107949","url":null,"abstract":"Presentation attack detection (PAD) methods are commonly evaluated using metrics based on the predicted labels. This is a limitation, especially for more elusive methods based on deep learning which can freely learn the most suitable features. Though often being more accurate, these models operate as complex black boxes which makes the inner processes that sustain their predictions still baffling. Interpretability tools are now being used to delve deeper into the operation of machine learning methods, especially artificial networks, to better understand how they reach their decisions. In this paper, we make a case for the integration of interpretability tools in the evaluation of PAD. A simple model for face PAD, based on convolutional neural networks, was implemented and evaluated using both traditional metrics (APCER, BPCER and EER) and interpretability tools (Grad-CAM), using data from the ROSE Youtu video collection. The results show that interpretability tools can capture more completely the intricate behavior of the implemented model, and enable the identification of certain properties that should be verified by a PAD method that is robust, coherent, meaningful, and can adequately generalize to unseen data and attacks. One can conclude that, with further efforts devoted towards higher objectivity in interpretability, this can be the key to obtain deeper and more thorough PAD performance evaluation setups.","PeriodicalId":174654,"journal":{"name":"2020 8th International Workshop on Biometrics and Forensics (IWBF)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132470742","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

IWBF 2020 Author Index IWBF 2020作者索引

2020 8th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2020-04-01 DOI: 10.1109/iwbf49977.2020.9107947

引用次数: 0

Efficient Fingervein Sample Image Encryption 高效手指静脉样本图像加密

2020 8th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2020-04-01 DOI: 10.1109/IWBF49977.2020.9107943

Sanjay Shekhawat, H. Hofbauer, B. Prommegger, A. Uhl

引用次数: 5