2017 IEEE International Joint Conference on Biometrics (IJCB)最新文献

Learning-based local-patch resolution reconstruction of iris smart-phone images 基于学习的虹膜智能手机图像局部补丁分辨率重建

2017 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2017-10-01 DOI: 10.1109/BTAS.2017.8272771

F. Alonso-Fernandez, R. Farrugia, J. Bigün

引用次数: 4

Iris and periocular recognition in arabian race horses using deep convolutional neural networks 用深度卷积神经网络识别阿拉伯赛马的虹膜和眼周

2017 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2017-10-01 DOI: 10.1109/BTAS.2017.8272736

Mateusz Trokielewicz, M. Szadkowski

引用次数: 9

Fingerprint pose estimation based on faster R-CNN 基于更快R-CNN的指纹姿态估计

2017 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2017-10-01 DOI: 10.1109/BTAS.2017.8272707

J. Ouyang, Jianjiang Feng, Jiwen Lu, Zhenhua Guo, Jie Zhou

引用次数: 8

Deep expectation for estimation of fingerprint orientation fields 基于深度期望的指纹方向场估计

2017 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2017-10-01 DOI: 10.1109/BTAS.2017.8272697

Patrick Schuch, Simon-Daniel Schulz, C. Busch

引用次数: 11

Single 2D pressure footprint based person identification 基于单个2D压力足迹的人员识别

2017 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2017-10-01 DOI: 10.1109/BTAS.2017.8272725

Xinnian Wang, Huiyu Wang, Qi-Chang Cheng, Namusisi Linda Nankabirwa, Zhang Tao

{"title":"Single 2D pressure footprint based person identification","authors":"Xinnian Wang, Huiyu Wang, Qi-Chang Cheng, Namusisi Linda Nankabirwa, Zhang Tao","doi":"10.1109/BTAS.2017.8272725","DOIUrl":"https://doi.org/10.1109/BTAS.2017.8272725","url":null,"abstract":"Footprints carry many important human characteristics, such as anatomical structures of the foot, skin texture of the foot sole, standing or walking habits, and so on. They play vital roles in forensic investigations as an alternative biometric. In this paper, we propose an automatic footprint based person identification method using a single bare or socked footprint, which differs from the existing bare footprint based methods. An area rank filter is put forward to remove dust noises. Pressure distribution prior of the hind footprint is proposed to estimate the footprint direction. Both Geometrical Shape Spectrum Representation and Pressure Radial Gradient Map are proposed to represent a footprint in views of geometric shape, anatomical structure and one's standing or walking habits, which are also rotation and translation invariant. We also put forward a regional confidence value based method to compute the similarity values between two footprints. Additionally, we have constructed an evaluation dataset composed of 480 subjects and 19200 bare or socked footprints. Experimental results show that the proposed algorithm outperforms state of the-art algorithms, and its recognition rate reaches 98.75%.","PeriodicalId":372008,"journal":{"name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128249469","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: 7

Boosting cross-age face verification via generative age normalization 通过生成年龄归一化促进跨年龄人脸验证

2017 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2017-10-01 DOI: 10.1109/BTAS.2017.8272698

G. Antipov, M. Baccouche, J. Dugelay

引用次数: 21

Cross-pose landmark localization using multi-dropout framework 基于多dropout框架的交叉位姿地标定位

2017 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2017-10-01 DOI: 10.1109/BTAS.2017.8272722

G. Hsu, Cheng-Hua Hsieh

{"title":"Cross-pose landmark localization using multi-dropout framework","authors":"G. Hsu, Cheng-Hua Hsieh","doi":"10.1109/BTAS.2017.8272722","DOIUrl":"https://doi.org/10.1109/BTAS.2017.8272722","url":null,"abstract":"We propose the Multiple Dropout Framework (MDF) for facial landmark localization across large poses. Unlike most landmark detectors only work for poses less than 45 degree in yaw, the proposed MDF works for pose as large as 90 degree, i.e., full profile. In the proposed MDF, the Single Shot Multibox Detector (SSD) [10] is tailored for fast and precise face detection. Given an SSD detected face, a Multiple Dropout Network (MDN) is proposed to classify the face into either frontal or profile pose, and for each pose another MDN is configured for detecting pose-oriented landmarks. As the MDF framework contains one MDN (pose) classifier and two MDN (landmark) regressors, this study aims to determine the MDN structures and settings appropriate for handling classification and regression tasks. The MDN framework demonstrates the following advantages and observations. (1) Landmark detection across poses can be better approached by incorporating a pose classifier with pose-oriented landmark regressors. (2) Multiple dropouts are required for stabilizing the training of regressor networks. (3) Additional hand-crafted features, such as the Local Binary Pattern (LBP), can improve the accuracy of landmark localization. (4) Face profiling is a powerful tool for offering a large cross-pose training set. A comparison study on benchmark databases shows that the MDN delivers a competitive performance to the state-of-the-art approaches for face alignment across large poses.","PeriodicalId":372008,"journal":{"name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133256202","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: 8

A decision-level fusion strategy for multimodal ocular biometric in visible spectrum based on posterior probability 基于后验概率的多模态眼生物识别决策级融合策略

2017 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2017-10-01 DOI: 10.1109/BTAS.2017.8272772

Abhijit Das, U. Pal, M. A. Ferrer-Ballester, M. Blumenstein

引用次数: 3

Optimizing resources on smartphone gait recognition 智能手机步态识别资源优化

2017 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2017-10-01 DOI: 10.1109/BTAS.2017.8272679

Pablo Fernández López, Jorge Sanchez-Casanova, Paloma Tirado-Martin, J. Liu-Jimenez

引用次数: 18

Gender and ethnicity classification of Iris images using deep class-encoder 基于深度分类编码器的虹膜图像性别和种族分类

2017 IEEE International Joint Conference on Biometrics (IJCB) Pub Date : 2017-10-01 DOI: 10.1109/BTAS.2017.8272755

Maneet Singh, Shruti Nagpal, Mayank Vatsa, Richa Singh, A. Noore, A. Majumdar

引用次数: 26