Developing a non-intrusive biometric environment

L. Middleton, D. Wagg, A. Bazin, J. Carter, M. Nixon
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引用次数: 14

Abstract

The development of large scale biometric systems requires experiments to be performed on large amounts of data. Existing capture systems are designed for fixed experiments and are not easily scalable. In this scenario even the addition of extra data is difficult. We developed a prototype biometric tunnel for the capture of non-contact biometrics. It is self contained and autonomous. Such a configuration is ideal for building access or deployment in secure environments. The tunnel captures cropped images of the subject's face and performs a 3D reconstruction of the person's motion which is used to extract gait information. Interaction between the various parts of the system is performed via the use of an agent framework. The design of this system is a trade-off between parallel and serial processing due to various hardware bottlenecks. When tested on a small population the extracted features have been shown to be potent for recognition. We currently achieve a moderate throughput of approximate 15 subjects an hour and hope to improve this in the future as the prototype becomes more complete
开发非侵入性生物识别环境
大规模生物识别系统的发展需要对大量数据进行实验。现有的捕获系统是为固定实验设计的,不容易扩展。在这种情况下,甚至很难添加额外的数据。我们开发了一个原型生物识别隧道,用于捕获非接触式生物识别。它是独立自主的。这种配置非常适合在安全环境中构建访问或部署。隧道捕获受试者面部的裁剪图像,并对人的运动进行3D重建,用于提取步态信息。系统各部分之间的交互是通过使用代理框架来完成的。由于各种硬件瓶颈,该系统的设计是并行和串行处理之间的权衡。当在小群体中进行测试时,所提取的特征已被证明是有效的识别。我们目前实现了大约每小时15个受试者的中等吞吐量,并希望在未来随着原型变得更加完整而改进这一点
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