人体红外辐射及温度特性与呼吸等生理活动密切相关。针对远程监测需要，提出了一种基于面部红外图像分析的在体呼吸监测方法。为了提高红外热成像中鼻孔区域识别及跟踪精度，研究了基于Harris角点法的提取方法，及基于光流场方法的特征跟踪识别方法；分析对比了不同环境中在体呼吸信号时频特征及统计参数。实验结果表明，本文提出的方法可以准确监测在体呼吸信号，分析呼吸模式变化，为红外热成像方法在临床医学的应用提供了参考。

The body infrared radiation characteristics are related to physiological activities such as respiration. We developed a novel approach to remotely monitor respiration by using the time-series infrared thermography of face. To improve the accuracy and robustness， the algorithm is researched based on Harris corner detection and optical flow field tracking method， which enhances the accuracy of the nostril region tracking. We demonstrate the approach by monitoring the respiratory of human in different environment and evaluating its time-frequency characteristics and statistical parameters. The results show that the approach can reliably monitor the real-time respiration and its pattern. That would be helpful for the clinical application of the infrared thermography on monitoring physiological status.