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

点击翻译按钮获取中文摘要

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.