2015 International Conference on Biometrics (ICB)最新文献_第2页

Swipe gesture based Continuous Authentication for mobile devices 基于滑动手势的移动设备连续认证

2015 International Conference on Biometrics (ICB) Pub Date : 2015-05-19 DOI: 10.1109/ICB.2015.7139110

Soumik Mondal, Patrick A. H. Bours

引用次数: 39

Fast and robust self-training beard/moustache detection and segmentation 快速和鲁棒的自我训练胡子/小胡子检测和分割

2015 International Conference on Biometrics (ICB) Pub Date : 2015-05-19 DOI: 10.1109/ICB.2015.7139066

T. Le, Khoa Luu, M. Savvides

{"title":"Fast and robust self-training beard/moustache detection and segmentation","authors":"T. Le, Khoa Luu, M. Savvides","doi":"10.1109/ICB.2015.7139066","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139066","url":null,"abstract":"Facial hair detection and segmentation play an important role in forensic facial analysis. In this paper, we propose a fast, robust, fully automatic and self-training system for beard/moustache detection and segmentation in challenging facial images. In order to overcome the limitations of illumination, facial hair color and near-clear shaving, our facial hair detection self-learns a transformation vector to separate a hair class and a non-hair class from the testing image itself. A feature vector, consisting of Histogram of Gabor (HoG) and Histogram of Oriented Gradient of Gabor (HOGG) at different directions and frequencies, is proposed for both beard/moustache detection and segmentation in this paper. A feature-based segmentation is then proposed to segment the beard/moustache from a region on the face that is discovered to contain facial hair. Experimental results have demonstrated the robustness and effectiveness of our proposed system in detecting and segmenting facial hair in images drawn from three entire databases i.e. the Multiple Biometric Grand Challenge (MBGC) still face database, the NIST color Facial Recognition Technology FERET database and a large subset from Pinellas County database.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114359182","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

Combining view-based pose normalization and feature transform for cross-pose face recognition 结合基于视图的姿态归一化和特征变换的交叉姿态人脸识别

2015 International Conference on Biometrics (ICB) Pub Date : 2015-05-19 DOI: 10.1109/ICB.2015.7139114

Hua Gao, H. K. Ekenel, R. Stiefelhagen

{"title":"Combining view-based pose normalization and feature transform for cross-pose face recognition","authors":"Hua Gao, H. K. Ekenel, R. Stiefelhagen","doi":"10.1109/ICB.2015.7139114","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139114","url":null,"abstract":"Automatic face recognition across large pose changes is still a challenging problem. Previous solutions apply a transform in image space or feature space for normalizing the pose mismatch. For feature transform, the feature vector extracted on a probe facial image is transferred to match the gallery condition with regression models. Usually, the regression models are learned from paired gallery-probe conditions, in which pose angles are known or accurately estimated. The solution based on image transform is able to handle continuous pose changes, yet the approach suffers from warping artifacts due to misalignment and self-occlusion. In this work, we propose a novel approach, which combines the advantage of both methods. The algorithm is able to handle continuous pose mismatch in gallery and probe set, mitigating the impact of inaccurate pose estimation in feature-transform-based method. We evaluate the proposed algorithm on the FERET face database, where the pose angles are roughly annotated. Experimental results show that our proposed method is superior to solely image/feature transform methods, especially when the pose angle difference is large.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"295 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123117225","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

Attribute preserved face de-identification 属性保留人脸去识别

2015 International Conference on Biometrics (ICB) Pub Date : 2015-05-19 DOI: 10.1109/ICB.2015.7139096

Amin Jourabloo, Xi Yin, Xiaoming Liu

引用次数: 85

A biomechanical approach to iris normalization 虹膜归一化的生物力学方法

2015 International Conference on Biometrics (ICB) Pub Date : 2015-05-19 DOI: 10.1109/ICB.2015.7139041

Inmaculada Tomeo-Reyes, A. Ross, A. Clark, V. Chandran

{"title":"A biomechanical approach to iris normalization","authors":"Inmaculada Tomeo-Reyes, A. Ross, A. Clark, V. Chandran","doi":"10.1109/ICB.2015.7139041","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139041","url":null,"abstract":"The richness of the iris texture and its variability across individuals make it a useful biometric trait for personal authentication. One of the key stages in classical iris recognition is the normalization process, where the annular iris region is mapped to a dimensionless pseudo-polar coordinate system. This process results in a rectangular structure that can be used to compensate for differences in scale and variations in pupil size. Most iris recognition methods in the literature adopt linear sampling in the radial and angular directions when performing iris normalization. In this paper, a biomechanical model of the iris is used to define a novel nonlinear normalization scheme that improves iris recognition accuracy under different degrees of pupil dilation. The proposed biomechanical model is used to predict the radial displacement of any point in the iris at a given dilation level, and this information is incorporated in the normalization process. Experimental results on the WVU pupil light reflex database (WVU-PLR) indicate the efficacy of the proposed technique, especially when matching iris images with large differences in pupil size.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126540330","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: 22

Latent fingerprint match using Minutia Spherical Coordinate Code 潜在指纹匹配使用Minutia球面坐标代码

2015 International Conference on Biometrics (ICB) Pub Date : 2015-05-19 DOI: 10.1109/ICB.2015.7139061

Fengde Zheng, Chunyu Yang

引用次数: 9

Discriminative regularized metric learning for person re-identification 人再识别的判别正则度量学习

2015 International Conference on Biometrics (ICB) Pub Date : 2015-05-19 DOI: 10.1109/ICB.2015.7139075

Venice Erin Liong, Yongxin Ge, Jiwen Lu

引用次数: 6

Exploring dorsal finger vein pattern for robust person recognition 探索手指背静脉模式对人的鲁棒识别

2015 International Conference on Biometrics (ICB) Pub Date : 2015-05-19 DOI: 10.1109/ICB.2015.7139059

Ramachandra Raghavendra, C. Busch

{"title":"Exploring dorsal finger vein pattern for robust person recognition","authors":"Ramachandra Raghavendra, C. Busch","doi":"10.1109/ICB.2015.7139059","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139059","url":null,"abstract":"Finger vein based biometric recognition has increasingly generated interest amongst biometric researchers because of the accuracy, robustness and anti-spoofing propertie. Prior efforts the are documented in the finger vein biometrics literature have only investigated the ventral vein pattern that is formed on the lower part of the finger underneath the skin surface. This paper investigates a new finger vein biometric approach by exploring the vein pattern that is present in the dorsal finger region. Thus, the dorsal finger vein pattern can be used as an independent biometric characteristic useful for the recognition of the target subject. We presented a complete automated approach with the key steps of image capturing, Region of Interest (ROI) extraction, pre-processing to enhance the vein pattern, feature extraction and comparison. This paper also introduces a new database of dorsal finger vein patterns from 125 subjects that resulted in 500 unique fingers with 10 samples each that results in a total of 5000 dorsal finger vein samples. Extensive experiments carried out on our new dorsal finger vein database achieve promising accuracy and thereby provide new insights on this new biometric approach.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115860242","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: 23

Band selection for Gabor feature based hyperspectral palmprint recognition 基于Gabor特征的高光谱掌纹识别波段选择

2015 International Conference on Biometrics (ICB) Pub Date : 2015-05-19 DOI: 10.1109/ICB.2015.7139104

L. Shen, Ziyi Dai, Sen Jia, Meng Yang, Zhihui Lai, Shiqi Yu

{"title":"Band selection for Gabor feature based hyperspectral palmprint recognition","authors":"L. Shen, Ziyi Dai, Sen Jia, Meng Yang, Zhihui Lai, Shiqi Yu","doi":"10.1109/ICB.2015.7139104","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139104","url":null,"abstract":"Hyperspectral imaging has recently been introduced into face and palmprint recognition and is now drawing much attention of researchers in this area. Compared to simple 2D imaging technology, hyperspectral image can bring much more information. Due to its ablity to jointly explore the spatial-spectral domain, 3D Gabor wavelets have been successfully applied for hyperspectral palmprint recognition. In this approach, a set of 52 three-dimensional Gabor wavelets with different frequencies and orientations were designed and convolved with the cube to extract discriminative information in the joint spatial-spectral domain. However, there is also much redundancy among the hyperpecstral data, which makes the feature extraction computationally expensive. In this paper, we propose to use AP (affinity propagation) based clustering approach to select representative band images from available large data. As the number of bands has been greatly reduced, the feature extraction process can be efficiently speed up. Experimental results on the publicly available HK-PolyU hyperspectral palmprint database show that the proposed approach not only improves the efficiency, but also reduces the EER of 3D Gabor feature based method from 4% to 3.26%.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116292089","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: 10

Palm region extraction for contactless palmprint recognition 面向非接触式掌纹识别的掌纹区域提取

2015 International Conference on Biometrics (ICB) Pub Date : 2015-05-19 DOI: 10.1109/ICB.2015.7139058

Koichi Ito, Takuto Sato, Shoichiro Aoyama, S. Sakai, Shusaku Yusa, T. Aoki

引用次数: 23