CAREER: Human Recognition - Models for Biometric Pattern Representation, Individuality, Indexing and Fusion

职业：人类识别 - 生物识别模式表示、个性、索引和融合模型

• 批准号: 0642554
• 负责人: Arun Ross
• 金额: $ 54万
• 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: 2007
• 资助国家: 美国
• 起止时间: 2007-05-01 至 2013-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0642554&HistoricalAwards=false
• 关键词: CAREER; Human; Recognition; Models; Biometric

The process of establishing human identity based on the physical (e.g.,fingerprints) or behavioral (e.g., gait) attributes of an individual constitutes the core of biometrics. Despite the successful deployment of biometric systems in several applications, a number of fundamental issues in biometrics are yet to be addressed in a comprehensive fashion.Indeed, establishing identity through biometrics is a complex and difficult problem due to the intrinsic challenges associated with the technology. The objective of this research project is to systematically develop methods to overcome the limitations of existing biometric systems, thereby advancing the state of the art in this field. In this regard, the following tasks are being conducted: (a) modeling the biometric patterns of an individual using analysis-by-synthesis schemes, individuality analysis and manifold geometry; (b) designing efficient indexing methods for the rapid retrieval of identities from a large repository of biometric patterns; (c) enhancing the information content of biometric patterns using multibiometric fusion techniques; and (d) evaluating the performance of the aforementioned tasks on real-world biometric datasets. The models and techniques generated in this work are also applicable to other domains in pattern recognition and computer vision.The results of this research project are expected to have a positive impact on the design and development of large-scale multibiometric systems for identity recognition management. In addition, the research activity will enhance the current biometrics curricula, engage students in cutting-edge research and promote use and effectiveness of biometric technology in diverse applications. The project's Web site (http://www.csee.wvu.edu/~ross/biometrics/) will be used for results and information dissemination to broad communities of researchers, educators, students and biometrics practitioners.

建立基于物理的人类身份的过程（例如，指纹）或行为（例如，步态）属性构成了生物测定的核心。尽管生物特征识别系统已成功应用于多个领域，但生物特征识别中的一些基本问题仍有待全面解决。事实上，由于与该技术相关的内在挑战，通过生物特征识别建立身份是一个复杂而困难的问题。该研究项目的目标是系统地开发克服现有生物识别系统局限性的方法，从而推进该领域的最新技术。在这方面，正在进行下列工作：（a）利用综合分析方案、个性分析和流形几何学建立个人生物特征模式的模型;（B）设计有效的索引方法，以便从大量生物特征模式储存库中迅速检索身份;（c）利用多种生物特征融合技术提高生物特征模式的信息内容;以及（d）评估上述任务在真实世界生物测定数据集上的性能。本研究所提出的模型和技术也可应用于模式识别和计算机视觉等领域，对大规模多生物特征身份识别系统的设计和开发具有积极意义。此外，研究活动将加强目前的生物识别课程，让学生参与尖端研究，并促进生物识别技术在各种应用中的使用和有效性。该项目的网址（http：//www.csee.wvu.edu/biometrics/）将用于向广大研究人员、教育工作者、学生和生物统计学从业人员传播成果和信息。