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Infrared Face Recognition by Using Blood Perfusion Data

机译:利用血液灌注数据进行红外人脸识别

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摘要

This paper presents a blood perfusion model of human faces based on thermodynamics and thermal physiology. The target is to convert the facial temperature data which are liable to ambient temperature into consistent blood perfusion data in order to improve the performance of infrared (IR) face recognition. Our large number of experiments has demonstrated that the blood perfusion data are less sensitive to ambient temperature if the human bodies are in steady state, and the real data testing demonstrated that the performance by means of blood perfusion data is significantly superior to that via temperature data in terms of recognition rate.
机译:本文提出了基于热力学和热生理学的人脸血液灌注模型。目标是将容易受到环境温度影响的面部温度数据转换为一致的血液灌注数据,以提高红外(IR)面部识别的性能。我们的大量实验表明,如果人体处于稳定状态,则血液灌注数据对环境温度的敏感性较低;而实际数据测试表明,通过血液灌注数据获得的性能明显优于通过温度数据获得的性能。在识别率方面。

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