A robust feature selection method for noncontact biometrics based on Laser Doppler Vibrometry

P. Lai, J. O’Sullivan, M. Chen, E. Sirevaag, A. D. Kaplan, J. Rohrbaugh
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引用次数: 18

Abstract

We propose a new biometric approach based on cardiovascular signals recorded using laser Doppler vibrometry (LDV) with a robust feature selection method. A novel feature selection method provides robustness against physiological variability of a given individual. LDV signals were collected from 191 individuals under controlled conditions during three sessions, each at intervals of one week to six months. The methods described here are based on a time-frequency decomposition of the LDV signal in which the log-power of the decomposition values are used as features. In identity verification tasks, equal error rates in the single digits can be achieved with testing periods as short as 4 s.
基于激光多普勒振动法的非接触生物特征鲁棒选择方法
我们提出了一种新的基于激光多普勒振动仪(LDV)记录的心血管信号的生物识别方法,并采用鲁棒特征选择方法。一种新的特征选择方法提供了对给定个体生理变异性的鲁棒性。在控制条件下,在三个疗程中,每隔一周到六个月,从191个个体中收集LDV信号。这里描述的方法是基于LDV信号的时频分解,其中分解值的对数幂作为特征。在身份验证任务中,可以在短至4秒的测试周期内实现相同的个位数错误率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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