用低帧率单色指纹视频实现身份认证与心率检测
User Authentication and Vital Signs Extraction from Low-Frame-Rate and Monochrome No-contact Fingerprint Captures
- 用低成本设备采集蓝光单色低帧率指纹视频
- 心率估计和身份识别误差均较低
- 适合资源受限场景的生物特征安全应用
我们研究利用普通指纹采集设备捕获的低帧率单色（蓝光）指尖视频，实现用户身份识别与生命体征提取。这些视频基于光电容积脉搏波描记法（PPG），常用于测量心率等生命体征。以往研究多依赖高帧率、多波长传感器（如红外、红光或RGB），而我们的初步结果表明，即使使用低帧率数据，仍可实现用户识别与生命体征提取。初步结果显示心率估算与身份认证误差均较低，表明该方法在生物特征系统中具有潜力。我们预计进一步优化将提升精度，推动医疗与安全领域应用。
原文摘要 · Abstract (English)
We present our work on leveraging low-frame-rate monochrome (blue light) videos of fingertips, captured with an off-the-shelf fingerprint capture device, to extract vital signs and identify users. These videos utilize photoplethysmography (PPG), commonly used to measure vital signs like heart rate. While prior research predominantly utilizes high-frame-rate, multi-wavelength PPG sensors (e.g., infrared, red, or RGB), our preliminary findings demonstrate that both user identification and vital sign extraction are achievable with the low-frame-rate data we collected. Preliminary results are promising, with low error rates for both heart rate estimation and user authentication. These results indicate promise for effective biometric systems. We anticipate further optimization will enhance accuracy and advance healthcare and security.
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