多光谱面部生物识别技术在门禁中的应用

K. Lai, S. Samoil, S. Yanushkevich
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引用次数: 5

摘要

本文演示了使用RGB、深度和红外等多光谱传感器获取的面部生物特征如何在自动化和半自动门禁系统的用户授权过程中协助数据积累。这些数据用于人的身份验证,以及面部温度估计。我们利用使用廉价的RGB-D传感器拍摄的深度数据来找到受试者的头部姿势。这允许选择包含面部识别和面部温度读数的正面头部姿势的视频帧。正面视图帧的使用提高了人脸识别的效率,而相应的同步红外视频帧允许对感兴趣的面部区域进行更有效的温度估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-spectral facial biometrics in access control
This paper 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.
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