Abstract

This paper presents a design and development of a low power consumption, and low cost, human identification system using a pyroelectric infrared (PIR) sensor whose visibility is modulated by a Fresnel lens array. The optimal element number of the lens array for the identification system was investigated and the experimental results suggest that the lens array with more elements can yield a better performance in terms of identification and false alarm rates. The other parameters of the system configuration such as the height of sensor location and sensor-to-object distance were also studied to improve spectral distinctions among sensory data of human objects. The identification process consists of two parts: training and testing. For the data training, we employed a principal components regression (PCR) method to cluster data with respect to different registered objects at different speed levels. The feature data of different objects walking along the same path in training yet at random speeds are then tested against the pre-trained clusters to decide whether the target is registered, and which member of the registered group it is.

© 2006 Optical Society of America

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References

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  1. M. Planck, "On the law of distribution of energy in the normal spectrum," Annalen der Physik 4, 533 ff (1901).
  2. V. Spitzer, M. Ackerman, A. Scherzinger, D. Whitlock, "The visible human male: A technical report," J. Am. Med. Assoc. 3, 118-130 (1996).
    [CrossRef]
  3. N. Kakuta, S. Yokoyama, M. Nakamura, "Estimation of radiative heat transfer using a geometric human model," IEEE Trans. Biomed. Eng. 48, 324-331 (2001).
    [CrossRef] [PubMed]
  4. Glolab Corporation, "Infrared parts manual," <a href= "http://www.glolab.com/pirparts/infrared.html">http://www.glolab.com/pirparts/infrared.html</a>
  5. U. Gopinathan, D. J. Brady, N. P. Pitsianis, "Coded apertures for efficient pyroelectric motion tracking," Opt. Express. 11, 2142-2152 (2003), <a href="http://www.opticsexpress.org/abstract.cfm?URI=OPEX-11-18-2142">http://www.opticsexpress.org/abstract.cfm?URI=OPEX-11-18-2142</a>
    [CrossRef] [PubMed]
  6. A. S. Sekmen, M. Wilkes, and K. Kawamura, "An application of passive human-robot interaction: human tracking based on attention distraction," IEEE Trans. Syst., Man Cybern. A 32, 248-259 (2002).
    [CrossRef]
  7. Q. Hao, D. J. Brady, B. D. Guenther, J. Burchett, M. Shankar, and S. Feller, "Human tracking with wireless distributed radial pyroelectric sensors," submitted to IEEE Sensors Journal.
  8. Anil K. Jain, Arun Ross, Salil Prabhakar, "An introduction to biometric recognition," IEEE Trans. Circuits Syst. Video Technol. 14, 4-20 (2004).
    [CrossRef]
  9. M. M. Trivedi, K. S. Huang, and I. Mikic, "Dynamic context capture and distributed video arrays for intelligent spaces," IEEE Trans. Syst., Man Cybern. A 35, 145-163 (2005).
    [CrossRef]
  10. J. L. Geisheimer, W. S. Marshall, and E. Greneker, "A continuous-wave (CW) radar for gait analysis," Proc. of IEEE. Signals, Systems and Computers 1, 843-838 (2001).
  11. Fresnel Technologies Inc., <a href= "http://www.fresneltech.com/arrays.html">http://www.fresneltech.com/arrays.html.</a>

Annalen der physik

M. Planck, "On the law of distribution of energy in the normal spectrum," Annalen der Physik 4, 533 ff (1901).

IEEE Trans. Circuits Syst. Video Technol

Anil K. Jain, Arun Ross, Salil Prabhakar, "An introduction to biometric recognition," IEEE Trans. Circuits Syst. Video Technol. 14, 4-20 (2004).
[CrossRef]

IEEE Trans. Syst., Man Cybern. A

M. M. Trivedi, K. S. Huang, and I. Mikic, "Dynamic context capture and distributed video arrays for intelligent spaces," IEEE Trans. Syst., Man Cybern. A 35, 145-163 (2005).
[CrossRef]

A. S. Sekmen, M. Wilkes, and K. Kawamura, "An application of passive human-robot interaction: human tracking based on attention distraction," IEEE Trans. Syst., Man Cybern. A 32, 248-259 (2002).
[CrossRef]

IEEE. Signals, Systems and Computers

J. L. Geisheimer, W. S. Marshall, and E. Greneker, "A continuous-wave (CW) radar for gait analysis," Proc. of IEEE. Signals, Systems and Computers 1, 843-838 (2001).

IEEE. Trans. Biomed. Eng.

N. Kakuta, S. Yokoyama, M. Nakamura, "Estimation of radiative heat transfer using a geometric human model," IEEE Trans. Biomed. Eng. 48, 324-331 (2001).
[CrossRef] [PubMed]

J. Am Med. Assoc.

V. Spitzer, M. Ackerman, A. Scherzinger, D. Whitlock, "The visible human male: A technical report," J. Am. Med. Assoc. 3, 118-130 (1996).
[CrossRef]

Opt. Express

U. Gopinathan, D. J. Brady, N. P. Pitsianis, "Coded apertures for efficient pyroelectric motion tracking," Opt. Express. 11, 2142-2152 (2003), <a href="http://www.opticsexpress.org/abstract.cfm?URI=OPEX-11-18-2142">http://www.opticsexpress.org/abstract.cfm?URI=OPEX-11-18-2142</a>
[CrossRef] [PubMed]

submitted to IEEE Sensors Journal

Q. Hao, D. J. Brady, B. D. Guenther, J. Burchett, M. Shankar, and S. Feller, "Human tracking with wireless distributed radial pyroelectric sensors," submitted to IEEE Sensors Journal.

Other

Glolab Corporation, "Infrared parts manual," <a href= "http://www.glolab.com/pirparts/infrared.html">http://www.glolab.com/pirparts/infrared.html</a>

Fresnel Technologies Inc., <a href= "http://www.fresneltech.com/arrays.html">http://www.fresneltech.com/arrays.html.</a>

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Figures (16)

Fig. 1.
Fig. 1.

Black-body radiation curve of human body at 37°C

Fig. 2.
Fig. 2.

Polar plot of response of the dual-element pyroelectric detector

Fig. 3.
Fig. 3.

Beams formed by a single lens on a lens array. The two beams correspond to each of the elements in a dual element detector.

Fig. 4.
Fig. 4.

Characteristic of field of view of Fresnal lens array. Each lens on the array creates two beams having a angular visibility of 3° separated by 1°.

Fig. 5.
Fig. 5.

Four different masks for selection of lens elements.

Fig. 6.
Fig. 6.

The diagram of the proposed identification system.

Fig. 7.
Fig. 7.

An experimental setup for human identification. The center of the sensor element is perpendicular to the path.

Fig. 8.
Fig. 8.

Output signals for two different individuals walking across the field of view of one sensor unit.

Fig. 9.
Fig. 9.

The spectra for two different individuals by performing the Fourier transform of the temporal signals in Fig. 8.

Fig. 10.
Fig. 10.

Each column is for different speed levels (fast, moderate, and slow, respectively). Each row is for different element numbers of Fresnel lens arrays (1, 5, and 11, respectively). Each subfigure contains 20 superimposed data sets which were gathered from 20 independent walks at the same speed. (a) The data sets of Jason. (a) The data sets of Bob.

Fig. 11.
Fig. 11.

The supervised clustering results upon 6 labels for 120 data sets collected from the sensor unit placed at the height of 80 cm. (a) Data from the sensor unit with the 1-element Fresnel lens array. (b) Data from the sensor unit with the 5-element Fresnel lens array. (c) Data from the sensor unit with the 11-element Fresnel lens array. (d) Probability density distributions of the clusters in (c).

Fig. 12.
Fig. 12.

The clustering results for 120 data sets from the sensor unit placed at the height of 120 cm. (a) Data from the sensor unit with the 11-element Fresnel lens array. (b) Probability density distributions of the clusters.

Fig. 13.
Fig. 13.

The clustering results for 120 data sets from the sensor unit placed at the height of 35 cm. (a) Data from the sensor unit with the 11 Fresnel lens array. (b) Probability density distributions of the clusters.

Fig. 14.
Fig. 14.

The identification results for a sensor unit with an 11-element lens array at the sensor-object distance of 2m. (a) The sensor unit is placed at the height of 120 cm. (b) The sensor unit is placed at the height of 80 cm. (c) The sensor unit is placed at the height of 35 cm.

Fig. 15.
Fig. 15.

The identification results for a sensor unit with the 11-element lens array at the sensor-object distance of 3m. (a) The sensor unit is placed at the height of 120 cm. (b) The sensor unit is placed at the height of 80 cm. (c) The sensor unit is placed at the height of 35 cm.

Fig. 16.
Fig. 16.

The identification results for the registered objects and unregistered objects at the same rejection threshold. (a) Recognition results for two registered objects: Bob and Jason. (b) Rejection results for two unregistered objects.

Tables (2)

Tables Icon

Table 1. Summary of characteristics of Fresnel lens array

Tables Icon

Table 2. Summary of identification false alarm rates with different sensor configurations.

Equations (20)

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I = S F .
S m × n = U m × m m × n V n × n T ,
= [ σ 1 σ 2 σ r 0 0 ] .
S = i = 1 r σ i u i v i T = σ 1 u 1 v 1 T + σ 2 u 2 v 2 T + + σ r u r v r T .
S S k = i = 1 k σ i u i v i T
= σ 1 u 1 v 1 T + σ 2 u 2 v 2 T + + σ k u k v k T ,
= U ˜ m × k ˜ k × k V ˜ k × n T
S TP T ,
T m × k = U ˜ m × k ˜ k × k ,
P = V ˜ n × k ,
SP = T .
I m × 1 = T m × k f k × 1 .
f k × 1 = ( T T T ) 1 T T I = ˜ 2 T T I ,
˜ 2 = [ 1 σ 1 2 1 σ 2 2 1 σ k 2 ] .
F n 1 = P n × k f k 1
= V ˜ n k ˜ 2 T T I
= V ˜ n × k ˜ 2 ( U ˜ m × k ˜ k × k ) T I
= V ˜ n × k ˜ 1 U ˜ m × k T I
x { H 0 , If max { p ( x H i ) } < γ H i : i = arg max i { p ( x H i ) } , otherwise
FAR = # of false sets # of testing sets

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