论文标题

访问控制中的多光谱面部生物识别技术

Multi-Spectral Facial Biometrics in Access Control

论文作者

Lai, K., Samoil, S., Yanushkevich, S. N.

论文摘要

这项研究表明,使用多光谱传感器(例如RGB,DEPTH和INDRARED)获得的面部生物识别技术如何在授权自动化和半自动化访问系统的用户的过程中协助数据积累。该数据具有人身份验证的目的以及面部温度估计。我们利用使用廉价的RGB-D传感器获取的深度数据来找到受试者的头部姿势。这允许选择包含额叶视线姿势的视频帧,以进行面部识别和面部温度读数。额叶视图框架的使用提高了面部识别的效率,而相应的同步IR视频框架可以对感兴趣的面部区域进行更有效的温度估算。此外,本研究报告了生物识别技术在生物医学和医疗保健解决方案中的新兴应用。包括对最近的试点项目的调查,涉及生物识别数据的新传感器以及人类生理和行为生物识别技术的新应用。它还显示了在自然和非接触式控制界面中使用生物识别技术的新的和有希望的视野,以进行手术控制,康复和可及性。

This study demonstrates how facial biometrics, acquired using multi-spectral sensors, such as RGB, depth, and infrared, assist the data accumulation in the process of authorizing users of automated and semi-automated access systems. This data serves the purposes of person authentication, as well as facial temperature estimation. We utilize depth data taken using an inexpensive RGB-D sensor to find the head pose of a subject. This allows the selection of video frames containing a frontal-view head pose for face recognition and face temperature reading. Usage of the frontal-view frames improves the efficiency of face recognition while the corresponding synchronized IR video frames allow for more efficient temperature estimation for facial regions of interest. In addition, this study reports emerging applications of biometrics in biomedical and health care solutions. Including surveys of recent pilot projects, involving new sensors of biometric data and new applications of human physiological and behavioral biometrics. It also shows the new and promising horizons of using biometrics in natural and contactless control interfaces for surgical control, rehabilitation and accessibility.

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