Feature-Level Fusion with Incomplete Data for Automatic Person Identification

本研究解决了目前的关键问题，在自动识别的人与不完整的数据使用多个特征。这项研究的成果不仅将为基础理论做出重大贡献，而且还将导致广泛的犯罪和恐怖主义预防应用，包括警察数据库搜索，访问控制，安全监控和监视。它们可以被警察和执法机构使用，也可以用于机场、政府大楼、军事设施甚至办公室和工厂的敏感区域。这将有助于减少犯罪，将国家安全提高到世界先进水平，并为澳大利亚安全行业创造新的产业和出口机会。

This research addresses the current key problems in automated person recognition with incomplete data using multiple traits. The outcomes of this research will not only make a significant contribution to fundamental theory but also result in a wide range of crime and terrorism preventing applications including police database searching, access control, security monitoring and surveillance. They can be used either by police and law enforcement agencies, or at places of airport, government buildings, military facilities and even sensitive areas in offices and factories. It will help reduce crime, enhance the security of the nation to a world-advanced level, and generate new industry and export opportunities for Australian security industry.