2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)最新文献

Inheritable Fisher vector feature for kinship verification 用于亲属关系验证的可遗传Fisher向量特征

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2015-12-17 DOI: 10.1109/BTAS.2015.7358768

Qingfeng Liu, Ajit Puthenputhussery, Chengjun Liu

引用次数: 41

Robust biometrics recognition using joint weighted dictionary learning and smoothed L0 norm

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2015-12-17 DOI: 10.1109/BTAS.2015.7358792

R. Khorsandi, A. Taalimi, M. Abdel-Mottaleb

{"title":"Robust biometrics recognition using joint weighted dictionary learning and smoothed L0 norm","authors":"R. Khorsandi, A. Taalimi, M. Abdel-Mottaleb","doi":"10.1109/BTAS.2015.7358792","DOIUrl":"https://doi.org/10.1109/BTAS.2015.7358792","url":null,"abstract":"In this paper, we present an automated system for robust biometric recognition based upon sparse representation and dictionary learning. In sparse representation, extracted features from the training data are used to develop a dictionary. Classification is achieved by representing the extracted features of the test data as a linear combination of entries in the dictionary. Dictionary learning for sparse representation has shown to improve the results in classification and recognition tasks since class labels can be used in obtaining the atoms of learnt dictionary. We propose a joint weighted dictionary learning which simultaneously learns from a set of training samples an over complete dictionary along with weight vectors that correspond to the atoms in the learnt dictionary. The components of the weight vector associated with an atom represent the relationship between the atom and each of the classes. The weight vectors and atoms are jointly obtained during the dictionary learning. In the proposed method, a constraint is imposed on the correlation between the obtained atoms that represent different classes to decrease the similarity between these atoms. In addition, we use smoothed L0 norm which is a fast algorithm to find the sparsest solution. Experiments conducted on the West Virginia University (WVU) and the University of Notre Dame (UND) datasets for ear recognition show that the proposed method outperforms other state-of-the-art classifiers.","PeriodicalId":404972,"journal":{"name":"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126123680","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: 5

ECG biometric authentication using a dynamical model 基于动态模型的心电生物识别认证

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2015-12-17 DOI: 10.1109/BTAS.2015.7358757

Abhijit Sarkar, A. L. Abbott, Zachary R. Doerzaph

引用次数: 12

Pose-robust face signature for multi-view face recognition 多视图人脸识别的姿态鲁棒性人脸签名

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2015-12-17 DOI: 10.1109/BTAS.2015.7358788

Pengfei Dou, Lingfeng Zhang, Yuhang Wu, S. Shah, I. Kakadiaris

引用次数: 24

Spoofing key-press latencies with a generative keystroke dynamics model 欺骗按键延迟与生成键击动力学模型

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2015-12-17 DOI: 10.1109/BTAS.2015.7358795

John V. Monaco, M. Ali, C. Tappert

引用次数: 22

e-BioSign tool: Towards scientific assessment of dynamic signatures under forensic conditions 电子生物签名工具:在法医条件下对动态签名进行科学评估

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2015-12-17 DOI: 10.1109/BTAS.2015.7358756

R. Vera-Rodríguez, Julian Fierrez, J. Ortega-Garcia, A. Acien, Rubén Tolosana

{"title":"e-BioSign tool: Towards scientific assessment of dynamic signatures under forensic conditions","authors":"R. Vera-Rodríguez, Julian Fierrez, J. Ortega-Garcia, A. Acien, Rubén Tolosana","doi":"10.1109/BTAS.2015.7358756","DOIUrl":"https://doi.org/10.1109/BTAS.2015.7358756","url":null,"abstract":"This paper presents a new tool specifically designed to carry out dynamic signature forensic analysis and give scientific support to forensic handwriting examiners (FHEs). Traditionally FHEs have performed forensic analysis of paper-based signatures for court cases, but with the rapid evolution of the technology, nowadays they are being asked to carry out analysis based on signatures acquired by digitizing tablets more and more often. In some cases, an option followed has been to obtain a paper impression of these signatures and carry out a traditional analysis, but there are many deficiencies in this approach regarding the low spatial resolution of some devices compared to original off-line signatures and also the fact that the dynamic information, which has been proved to be very discriminative by the biometric community, is lost and not taken into account at all. The tool we present in this paper allows the FHEs to carry out a forensic analysis taking into account both the traditional off-line information normally used in paper-based signature analysis, and also the dynamic information of the signatures. Additionally, the tool incorporates two important functionalities, the first is the provision of statistical support to the analysis by including population statistics for genuine and forged signatures for some selected features, and the second is the incorporation of an automatic dynamic signature matcher, from which a likelihood ratio (LR) can be obtained from the matching comparison between the known and questioned signatures under analysis.","PeriodicalId":404972,"journal":{"name":"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133907948","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: 5

Acquiring high-resolution face images in outdoor environments: A master-slave calibration algorithm 室外环境下高分辨率人脸图像的获取:主从校准算法

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2015-12-17 DOI: 10.1109/BTAS.2015.7358744

J. Neves, J. Moreno, Silvio Barra, Hugo Proença

{"title":"Acquiring high-resolution face images in outdoor environments: A master-slave calibration algorithm","authors":"J. Neves, J. Moreno, Silvio Barra, Hugo Proença","doi":"10.1109/BTAS.2015.7358744","DOIUrl":"https://doi.org/10.1109/BTAS.2015.7358744","url":null,"abstract":"Facial recognition at-a-distance in surveillance scenarios remains an open problem, particularly due to the small number of pixels representing the facial region. The use of pan-tilt-zoom (PTZ) cameras has been advocated to solve this problem, however, the existing approaches either rely on rough approximations or additional constraints to estimate the mapping between image coordinates and pan-tilt parameters. In this paper, we aim at extending PTZ-assisted facial recognition to surveillance scenarios by proposing a master-slave calibration algorithm capable of accurately estimating pan-tilt parameters without depending on additional constraints. Our approach exploits geometric cues to automatically estimate subjects height and thus determine their 3D position. Experimental results show that the presented algorithm is able to acquire high-resolution face images at a distance ranging from 5 to 40 meters with high success rate. Additionally, we certify the applicability of the aforementioned algorithm to biometric recognition through a face recognition test, comprising 20 probe subjects and 13,020 gallery subjects.","PeriodicalId":404972,"journal":{"name":"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"8 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132636052","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: 21

Post-mortem iris biometric analysis in Sus scrofa domesticus 家蝇死后虹膜生物特征分析

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2015-12-17 DOI: 10.1109/BTAS.2015.7358789

S. Saripalle, Adam McLaughlin, R. Krishna, A. Ross, R. Derakhshani

引用次数: 15

On humanoid robots imitating human touch gestures on the smart phone 在智能手机上模仿人类触摸手势的人形机器人

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2015-12-17 DOI: 10.1109/BTAS.2015.7358781

Sujit Poudel, Abdul Serwadda, V. Phoha

引用次数: 2

A Leap Password based verification system 基于Leap密码的验证系统

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) Pub Date : 2015-12-17 DOI: 10.1109/BTAS.2015.7358745

A. Chahar, Shivangi Yadav, Ishan Nigam, Richa Singh, Mayank Vatsa

引用次数: 25