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基于热释电红外传感器的人类识别影响因素研究。

Research on the Multiple Factors Influencing Human Identification Based on Pyroelectric Infrared Sensors.

机构信息

School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China.

School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China.

出版信息

Sensors (Basel). 2018 Feb 16;18(2):604. doi: 10.3390/s18020604.

DOI:10.3390/s18020604
PMID:29462908
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5854993/
Abstract

Analysis of the multiple factors affecting human identification ability based on pyroelectric infrared technology is a complex problem. First, we examine various sensed pyroelectric waveforms of the human body thermal infrared signal and reveal a mechanism for affecting human identification. Then, we find that the mechanism is decided by the distance, human target, pyroelectric infrared (PIR) sensor, the body type, human moving velocity, signal modulation mask, and Fresnel lens. The mapping relationship between the sensed waveform and multiple influencing factors is established, and a group of mathematical models are deduced which fuse the macro factors and micro factors. Finally, the experimental results show the macro-factors indirectly affect the recognition ability of human based on the pyroelectric technology. At the same time, the correctness and effectiveness of the mathematical models is also verified, which make it easier to obtain more pyroelectric infrared information about the human body for discriminating human targets.

摘要

基于热释电红外技术的人体识别能力影响因素分析是一个复杂的问题。首先，我们检测人体热红外信号的各种感知热释电波形，揭示影响人体识别的机制。然后，我们发现该机制由距离、人体目标、热释电红外（PIR）传感器、体型、人体移动速度、信号调制掩模和菲涅尔透镜决定。建立了感知波形与多个影响因素之间的映射关系，并推导出一组融合宏观因素和微观因素的数学模型。最后，实验结果表明，宏观因素通过热释电技术间接影响人体的识别能力。同时，还验证了数学模型的正确性和有效性，这使得更容易获得更多关于人体的热释电红外信息，从而对人体目标进行区分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/6450d1aaedd3/sensors-18-00604-g017.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/6450d1aaedd3/sensors-18-00604-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/b44aa9231e12/sensors-18-00604-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/087f7bfd8597/sensors-18-00604-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/3a27ca8dc3f0/sensors-18-00604-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/78c169627efd/sensors-18-00604-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/d843ce44888b/sensors-18-00604-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/5ac3d8ec727d/sensors-18-00604-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/ab8c979e55e2/sensors-18-00604-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/199d2b2c8776/sensors-18-00604-g014.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/e446245e71ca/sensors-18-00604-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f3/5854993/6450d1aaedd3/sensors-18-00604-g017.jpg

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