Multiple Human Tracking and Identification With Wireless Distributed Pyroelectric Sensor Systems

This paper presents a wireless distributed pyroelectric sensor system for tracking and identifying multiple humans based on their body heat radiation. This study aims to make pyroelectric sensors a low-cost alternative to infrared video sensors in thermal gait biometric applications. In this system, the sensor field of view (FOV) is specifically modulated with Fresnel lens arrays for functionality of tracking or identification, and the sensor deployment is chosen to facilitate the process of data-object-association. An Expectation-Maximization-Bayesian tracking scheme is proposed and implemented among slave, master, and host modules of a prototype system. Information fusion schemes are developed to improve the system identification performance for both individuals and multiple subjects. The fusion of thermal gait biometric information measured by multiple nodes is tested at four levels: sample, feature, score, and decision. Experimentally, the prototype system is able to simultaneously track two individuals in both follow-up and crossover scenarios with average tracking errors less than 0.5 m. The experimental results also demonstrate system's potential to be a reliable biometric system for the verification/identification of a small group of human subjects. The developed wireless distributed infrared sensor system can run as a standalone prisoner/patient monitoring system under any illumination conditions, as well as a complement for conventional video and audio human tracking and identification systems.

[1]  David J Brady,et al.  Fiber-optic localization by geometric space coding with a two-dimensional gray code. , 2005, Applied optics.

[2]  Jian-Shuen Fang,et al.  Real-time human identification using a pyroelectric infrared detector array and hidden Markov models. , 2006, Optics express.

[3]  Hans D. Schotten,et al.  Coded aperture imaging with multiple measurements , 1997 .

[4]  Jian-Shuen Fang,et al.  A pyroelectric infrared biometric system for real-time walker recognition by use of a maximum likelihood principal components estimation (MLPCE) method. , 2007, Optics express.

[5]  Qing Zhao,et al.  Distributed Learning in Wireless Sensor Networks , 2007 .

[6]  R.G. Baraniuk,et al.  Compressive Sensing [Lecture Notes] , 2007, IEEE Signal Processing Magazine.

[7]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

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

[9]  Mark S. Nixon,et al.  Covariate Analysis for View-Point Independent Gait Recognition , 2009, ICB.

[10]  Yu Hen Hu,et al.  Detection, classification, and tracking of targets , 2002, IEEE Signal Process. Mag..

[11]  Qi Hao,et al.  Human Tracking With Wireless Distributed Pyroelectric Sensors , 2006, IEEE Sensors Journal.

[12]  Bir Bhanu,et al.  Individual recognition using gait energy image , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Tieniu Tan,et al.  Human identification based on gait , 2005, The Kluwer international series on biometrics.

[14]  D. Mitchell Wilkes,et al.  An application of passive human-robot interaction: human tracking based on attention distraction , 2002, IEEE Trans. Syst. Man Cybern. Part A.

[15]  N. Sloane,et al.  Hadamard transform optics , 1979 .

[16]  Yaakov Bar-Shalom,et al.  Joint Probabilistic Data Association in Distributed Sensor Networks , 1985 .

[17]  Richard G. Baraniuk,et al.  Compressive Sensing , 2008, Computer Vision, A Reference Guide.

[18]  William T. Freeman,et al.  Constructing free-energy approximations and generalized belief propagation algorithms , 2005, IEEE Transactions on Information Theory.

[19]  N. Pitsianis,et al.  Coded apertures for efficient pyroelectric motion tracking. , 2003, Optics express.

[20]  John B. Burchett,et al.  Human-tracking systems using pyroelectric infrared detectors , 2006 .

[21]  D. Brady Multiplex sensors and the constant radiance theorem. , 2002, Optics letters.

[22]  Pascal Fua,et al.  3D tracking for gait characterization and recognition , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[23]  Patrick Pérez,et al.  Sequential Monte Carlo methods for multiple target tracking and data fusion , 2002, IEEE Trans. Signal Process..

[24]  Ramakant Nevatia,et al.  Tracking multiple humans in complex situations , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  Mohan M. Trivedi,et al.  Dynamic context capture and distributed video arrays for intelligent spaces , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[26]  S.S. Blackman,et al.  Multiple hypothesis tracking for multiple target tracking , 2004, IEEE Aerospace and Electronic Systems Magazine.

[27]  Yunhui Zheng,et al.  Nonadaptive Group testing based fiber sensor deployment for multiperson tracking , 2006, IEEE Sensors Journal.

[28]  M. Rashid,et al.  Pyroelectric detectors and their applications , 1989, Conference Record of the IEEE Industry Applications Society Annual Meeting,.

[29]  William Fitzgerald,et al.  A Bayesian approach to tracking multiple targets using sensor arrays and particle filters , 2002, IEEE Trans. Signal Process..

[30]  Andrew Sixsmith,et al.  Pyroelectric IR sensor arrays for fall detection in the older population , 2005 .

[31]  Kung Yao,et al.  Source localization and beamforming , 2002, IEEE Signal Process. Mag..

[32]  László Havasi,et al.  Higher order symmetry for non-linear classification of human walk detection , 2006, Pattern Recognit. Lett..

[33]  Jeffrey L. Krolik,et al.  Track association for over-the-horizon radar with a statistical ionospheric model , 2002, IEEE Trans. Signal Process..

[34]  Matthew J. Beal Variational algorithms for approximate Bayesian inference , 2003 .

[35]  Peter Willett,et al.  PMHT: problems and some solutions , 2002 .

[36]  Yaakov Bar-Shalom,et al.  Sonar tracking of multiple targets using joint probabilistic data association , 1983 .

[37]  D. Hatzinakos,et al.  Gait recognition: a challenging signal processing technology for biometric identification , 2005, IEEE Signal Processing Magazine.

[38]  S. Lang Pyroelectricity: From Ancient Curiosity to Modern Imaging Tool , 2005 .

[39]  Xiaodong Wang,et al.  Joint multiple target tracking and classification in collaborative sensor networks , 2004, ISIT.

[40]  Dorin Comaniciu,et al.  Kernel-Based Object Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[41]  Tieniu Tan,et al.  A survey on visual surveillance of object motion and behaviors , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[42]  Tarek Saadawi,et al.  Infrared pyroelectric sensor for detection of vehicular traffic using digital signal processing techniques , 1995 .

[43]  Rama Chellappa,et al.  A generic approach to simultaneous tracking and verification in video , 2002, IEEE Trans. Image Process..

[44]  Seong Jun Kang,et al.  Low-frequency response of pyroelectric sensors , 1998, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[45]  Xiaobai Sun,et al.  Reference structure tomography. , 2004, Journal of the Optical Society of America. A, Optics, image science, and vision.

[46]  Mark S. Nixon,et al.  Automatic Gait Recognition by Symmetry Analysis , 2001, AVBPA.

[47]  C. Stiller,et al.  Estimating motion in image sequences , 1999, IEEE Signal Process. Mag..

[48]  Feng Zhao,et al.  Information-driven dynamic sensor collaboration , 2002, IEEE Signal Process. Mag..