I/UCRC Phase II: Center for Identification Technology Research

I/UCRC 第二期：识别技术研究中心

• 批准号: 1650474
• 负责人: Matthew Valenti
• 金额: $ 50万
• 依托单位: West Virginia University Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1650474&HistoricalAwards=false
• 关键词: UCRC; Phase; II; Center; Identification

The Center for Identification Technology Research (CITeR) is an Industry/University Cooperative Research Center (I/UCRC) that is focused on developing and championing technologies and systems for managing the identity of individuals. Having a provable and verifiable identity is necessary for an individual to function in modern society. Working in partnership with government and industry stakeholders, CITeR advances the state of the art in human identification capabilities through coordinated university research related to providing, confirming, and determining identity. Its overall focus is on human analytics, identity science, biometric analysis, and technical implementation of privacy and policy. The WVU site provides innovations related to the increased use of biomolecular analysis (e.g., rapid DNA), cloud computing, mobile devices (e.g., smartphones), and video analytics. These innovations help to protect society and improve the national defense by providing pathways for identifying bad actors, while advancing the science of computing, analytics, and signal processing. CITeR engages graduate students and undergraduates in research, is active in outreach to K-12 students, and actively identifying and addressing the educational needs of next-generation professionals in the identification technology arena. The WVU site brings to the Center its first-ever undergraduate degree specifically focused on biometrics (B.S. in Biometric Systems) and is positioned in proximity to the expanding hub of biometric activity that has arisen in North Central West Virginia.The WVU Site will focus on four technical areas related to CITeR's technical area of Identity: (1) Biomolecular biometrics, (2) Cross-modal and cross-spectral matching, (3) Mobile and cloud biometrics, and (4) Video analytics. Recent advances in rapid DNA will be leveraged to provide tools and techniques to aid investigators, for instance, by providing the capability to extract small amounts of DNA from fingerprints. Cross-modal and cross-spectral matching provide improved ways to recognize subjects in unconstrained environments; for instance, by comparing thermal-to-visible images, thermal surveillance imagery can be compared with visible gallery imagery. Empowered by the cloud, mobile biometrics can improve convenience, but technical solutions must take privacy and security into account. Video analytics can allow subjects to be tracked across multiple camera views and allow their actions to be recognized.

识别技术研究中心（CITER）是一个行业/大学合作研究中心（I/UCRC），致力于开发和支持管理个人身份的技术和系统。 具有可证明和可验证的身份对于个人在现代社会中运作是必要的。 与政府和行业利益相关者合作，COTITER通过协调的大学研究与提供，确认和确定身份相关的大学研究来提高人类认同能力的最新状态。 它的总体重点是人类分析，身份科学，生物识别分析以及隐私和政策的技术实施。 WVU站点提供了与增加生物分子分析（例如快速DNA），云计算，移动设备（例如智能手机）和视频分析相关的创新。 这些创新通过提供确定不良行为者的途径，在推进计算，分析和信号处理科学的同时，有助于保护社会和改善国防。 Citer与研究生和大学生的研究生互动，积极向K-12学生推广，并积极识别和满足识别技术领域中下一代专业人员的教育需求。 The WVU site brings to the Center its first-ever undergraduate degree specifically focused on biometrics (B.S. in Biometric Systems) and is positioned in proximity to the expanding hub of biometric activity that has arisen in North Central West Virginia.The WVU Site will focus on four technical areas related to CITeR's technical area of​​ Identity: (1) Biomolecular biometrics, (2) Cross-modal and cross-spectral匹配，（3）移动和云生物识别技术以及（4）视频分析。 快速DNA的最新进展将被利用，以提供工具和技术来帮助研究人员，例如，提供从指纹中提取少量DNA的能力。 跨模式和跨光谱匹配提供了改进的方法，可以在不受约束的环境中识别受试者；例如，通过比较热能图像，可以将热监视图像与可见图库图像进行比较。在云中，移动生物识别技术可以提高便利性，但是技术解决方案必须考虑隐私和安全性。视频分析可以允许对受试者进行多个摄像机的跟踪，并允许识别其动作。

项目成果

Identical Twins Face Morph Database Generation

同卵双胞胎脸部变形数据库生成

• DOI: 10.1109/ijcb54206.2022.10007973
• 发表时间: 2022
• 期刊: Identical Twins Face Morph Database Generation
• 作者: OHaire, Kelsey;Soleymani, Sobhan;Chaudhary, Baaria;Dawson, Jeremy;Nasrabadi, Nasser M.
• 通讯作者: Nasrabadi, Nasser M.

Synthesis-Guided Feature Learning for Cross-Spectral Periocular Recognition

用于跨光谱眼周识别的综合引导特征学习

• DOI: 10.1109/fg52635.2021.9667086
• 发表时间: 2021
• 期刊: 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021
• 作者: Poster, Domenick;Nasrabadi, Nasser
• 通讯作者: Nasrabadi, Nasser

Adversarial Machine Learning in Malware Detection: Arms Race between Evasion Attack and Defense

• DOI: 10.1109/eisic.2017.21
• 发表时间: 2017-09
• 期刊: 2017 European Intelligence and Security Informatics Conference (EISIC)
• 作者: Lingwei Chen;Yanfang Ye;T. Bourlai

Unconstrained Face Detection and Open-Set Face Recognition Challenge

• DOI: 10.1109/btas.2017.8272759
• 发表时间: 2017-08
• 期刊: 2017 IEEE International Joint Conference on Biometrics (IJCB)
• 作者: Manuel Günther;Peiyun Hu;C. Herrmann;Chi-Ho Chan;Min Jiang;Shufan Yang;A. Dhamija;Deva Ramanan;J. Beyerer;J. Kittler;Mohamad Al Jazaery;Mohammad Iqbal Nouyed;G. Guo;Cezary Stankiewicz;T. Boult

Improving Face Recognition from Caption Supervision with Multi-Granular Contextual Feature Aggregation

• DOI: 10.1109/ijcb57857.2023.10448749
• 发表时间: 2023-08
• 期刊: 2023 IEEE International Joint Conference on Biometrics (IJCB)
• 作者: M. Hasan;N. Nasrabadi