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

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.

[1]  Chein-I Chang,et al.  Fisher's linear spectral mixture analysis , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Fangmin Li,et al.  Blind estimation of number of motion multi-human targets in wireless pyroelectric infrared sensor networks , 2013 .

[3]  Fang Zhu,et al.  Optimization of SVM Parameters Based on Artificial Immune Algorithm , 2012 .

[4]  A. Enis Çetin,et al.  Ambient assisted smart home design using vibration and PIR sensors , 2013, 2013 21st Signal Processing and Communications Applications Conference (SIU).

[5]  Luo Siwei,et al.  Performance of feedback BP networks , 2012 .

[6]  Cuiru Wang,et al.  A Human Action Recognition Algorithm Based on Semi-supervised Kmeans Clustering , 2011, Trans. Edutainment.

[7]  Suk Lee,et al.  Development of PIR sensor based indoor location detection system for smart home , 2006, 2006 SICE-ICASE International Joint Conference.

[8]  Zhen Sun,et al.  Fault Detection Using the Clustering-kNN Rule for Gas Sensor Arrays , 2016, Sensors.

[9]  Xiaomu Luo,et al.  Simultaneous Indoor Tracking and Activity Recognition Using Pyroelectric Infrared Sensors , 2017, Sensors.

[10]  Mariusz Kastek,et al.  PASSIVE INFRARED DETECTOR FOR SECURITY SYSTEMS DESIGN, ALGORITHM OF PEOPLE DETECTION AND FIELD TESTS RESULT , 2013 .

[11]  Liangxiao Jiang,et al.  A Novel Bayes Model: Hidden Naive Bayes , 2009, IEEE Transactions on Knowledge and Data Engineering.

[12]  Shintaro Yokoyama,et al.  Estimation of radiative heat transfer using a geometric human model , 2001, IEEE Transactions on Biomedical Engineering.

[13]  Jaeseok Yun,et al.  Human Movement Detection and Idengification Using Pyroelectric Infrared Sensors , 2014, Sensors.

[14]  Luca Benini,et al.  Tracking Motion Direction and Distance With Pyroelectric IR Sensors , 2010, IEEE Sensors Journal.

[15]  Tong Liu,et al.  Abnormal Activity Detection Using Pyroelectric Infrared Sensors , 2016, Sensors.

[16]  Jian Liu,et al.  Fusion of Different Height Pyroelectric Infrared Sensors for Person Identification , 2016, IEEE Sensors Journal.

[17]  Qi Hao,et al.  Multiple Human Tracking and Identification With Wireless Distributed Pyroelectric Sensor Systems , 2009, IEEE Systems Journal.

[18]  Qi Liu,et al.  A novel low-cost and small-size human tracking system with pyroelectric infrared sensor mesh network , 2014 .

[19]  Qi Hao,et al.  Active Compressive Sensing via Pyroelectric Infrared Sensor for Human Situation Recognition , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[20]  Xuemei Guo,et al.  Compressive classification of human motion using pyroelectric infrared sensors , 2014, Pattern Recognit. Lett..

[21]  Pengcheng Liu,et al.  Occupancy Inference Using Pyroelectric Infrared Sensors Through Hidden Markov Models , 2016, IEEE Sensors Journal.

[22]  Jian-Shuen Fang,et al.  Path-dependent human identification using a pyroelectric infrared sensor and fresnel lens arrays. , 2006, Optics express.

[23]  Wei Chu,et al.  A Noise-Robust FFT-Based Auditory Spectrum With Application in Audio Classification , 2008, IEEE Transactions on Audio, Speech, and Language Processing.

[24]  O. Urfaliglu,et al.  PIR-sensor based human motion event classification , 2008, 2008 IEEE 16th Signal Processing, Communication and Applications Conference.

[25]  Ahmet Sertbas,et al.  Evaluation of face recognition techniques using PCA, wavelets and SVM , 2010, Expert Syst. Appl..

[26]  Ji Xiong,et al.  Tracking and Recognition of Multiple Human Targets Moving in a Wireless Pyroelectric Infrared Sensor Network , 2014, Sensors.

[27]  M. Kastek,et al.  Passive infrared detector used for detection of very slowly moving of crawling people , 2008 .

[28]  Luca Benini,et al.  Enhancing the spatial resolution of presence detection in a PIR based wireless surveillance network , 2007, 2007 IEEE Conference on Advanced Video and Signal Based Surveillance.

[29]  David J. Brady,et al.  Tracking and imaging humans on heterogeneous infrared sensor arrays for tactical applications , 2002, SPIE Defense + Commercial Sensing.

[30]  K. Hashimoto,et al.  People count system using multi-sensing application , 1997, Proceedings of International Solid State Sensors and Actuators Conference (Transducers '97).

[31]  Hongan Wang,et al.  Missing Data Imputation: A Fuzzy K-means Clustering Algorithm over Sliding Window , 2009, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery.

[32]  Hirohide Haga,et al.  Human Position/Height Detection Using Analog Type Pyroelectric Sensors , 2005, EUC Workshops.