Abstract

The United States military is increasingly using infrared (IR) sensors to discriminate the actions and intentions of people being observed in an area of interest; however, there is currently inadequate modeling capability to a priori determine the effectiveness of IR sensors for these types of tasks. The U.S. Army’s NVTherm model is a military and industry standard sensor performance model that estimates target acquisition performance based on both the sensor design parameters and an empirically measured calibration factor to represent human observer performance. Historically the model has been calibrated by presenting static imagery to observers and measuring average probabilities of accomplishing the given task. The task of human activity discrimination, however, presents new challenges to the model, as “activity” inherently implies a dynamic scene where motion cues are essential in accomplishing the task. A series of studies has been completed in order to calibrate NVTherm for the task of human activity discrimination. The challenges involved in representing the human activity task, the establishment of new processing methods, and new standards for defining simple target metrics for complex imagery are discussed. The experiments that have supported the calculation of new calibration parameters are also described. These efforts have brought the U.S. Army significantly closer to having a sensor performance model validated for discriminating human activity with IR sensors.

© 2009 Optical Society of America

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References

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  1. U.S. Army Research Development and Engineering Command, Communications and Electronics Research Development and Engineering Center, Night Vision and Electronics Sensors Directorate (NVESD).
  2. U.S. Navy Office of Naval Research (ONR).
  3. S. Moyer and N. Devitt “Resolvable cycle criteria for identifying personnel based on clothing and armament variations,” Proc. SPIE 5784, 60-71 (2005).
    [CrossRef]
  4. S. Moyer, J. Hixson, T. C. Edwards, and K. Krapels, “Probability of identification of small hand-held objects for electro-optic forward-looking infrared systems,” Opt. Eng. 45, 063201(2006).
    [CrossRef]
  5. S. K. Moyer, E. Flug, T. C. Edwards, K. A. Krapels, and J. Scarborough “Identification of handheld objects for electro-optic/FLIR applications,” Proc. SPIE 5407, 116-126 (2004).
    [CrossRef]
  6. Night Vision Thermal and Image Processing (NVThermIP) Model Users Manual, Rev. 9, U.S. Army RDECOM, CERDEC, Night Vision and Electronic Sensors Directorate (2006).
  7. J. W. Goodman, Introduction to Fourier Optics, 2nd ed. (McGraw-Hill , 1996), pp. 4-22.
  8. R. Vollmerhausen and E. Jacobs “The targeting task performance (TTP) metric: a new model for predicting target acquisition performance,” U.S. Army CERDEC, Fort Belvoir, Va., Technical Report AMSEL-NV-TR-230, pp. 18-42, 47-51(2006).
  9. L-3 Communications Avenger FLIR information retrieved from http://www.cinele.com/pdfs/Avenger.pdf, 13 Oct. 2008.
  10. B. Miller, “Status of NVESD real-time imaging sensor simulation capability,” Proc. SPIE 5084, 170-177 (2005).
    [CrossRef]
  11. K. Krapels, R. G. Driggers, D. Deaver, S. K. Moyer, and J. Palmer, “Midwave infrared and visible sensor performance modeling: small craft identification discrimination criteria for maritime security,” Appl. Opt. 46, 7345-7353 (2007).
    [CrossRef] [PubMed]

2007 (1)

2006 (1)

S. Moyer, J. Hixson, T. C. Edwards, and K. Krapels, “Probability of identification of small hand-held objects for electro-optic forward-looking infrared systems,” Opt. Eng. 45, 063201(2006).
[CrossRef]

2005 (2)

S. Moyer and N. Devitt “Resolvable cycle criteria for identifying personnel based on clothing and armament variations,” Proc. SPIE 5784, 60-71 (2005).
[CrossRef]

B. Miller, “Status of NVESD real-time imaging sensor simulation capability,” Proc. SPIE 5084, 170-177 (2005).
[CrossRef]

2004 (1)

S. K. Moyer, E. Flug, T. C. Edwards, K. A. Krapels, and J. Scarborough “Identification of handheld objects for electro-optic/FLIR applications,” Proc. SPIE 5407, 116-126 (2004).
[CrossRef]

Deaver, D.

Devitt, N.

S. Moyer and N. Devitt “Resolvable cycle criteria for identifying personnel based on clothing and armament variations,” Proc. SPIE 5784, 60-71 (2005).
[CrossRef]

Driggers, R. G.

Edwards, T. C.

S. Moyer, J. Hixson, T. C. Edwards, and K. Krapels, “Probability of identification of small hand-held objects for electro-optic forward-looking infrared systems,” Opt. Eng. 45, 063201(2006).
[CrossRef]

S. K. Moyer, E. Flug, T. C. Edwards, K. A. Krapels, and J. Scarborough “Identification of handheld objects for electro-optic/FLIR applications,” Proc. SPIE 5407, 116-126 (2004).
[CrossRef]

Flug, E.

S. K. Moyer, E. Flug, T. C. Edwards, K. A. Krapels, and J. Scarborough “Identification of handheld objects for electro-optic/FLIR applications,” Proc. SPIE 5407, 116-126 (2004).
[CrossRef]

Goodman, J. W.

J. W. Goodman, Introduction to Fourier Optics, 2nd ed. (McGraw-Hill , 1996), pp. 4-22.

Hixson, J.

S. Moyer, J. Hixson, T. C. Edwards, and K. Krapels, “Probability of identification of small hand-held objects for electro-optic forward-looking infrared systems,” Opt. Eng. 45, 063201(2006).
[CrossRef]

Jacobs, E.

R. Vollmerhausen and E. Jacobs “The targeting task performance (TTP) metric: a new model for predicting target acquisition performance,” U.S. Army CERDEC, Fort Belvoir, Va., Technical Report AMSEL-NV-TR-230, pp. 18-42, 47-51(2006).

Krapels, K.

K. Krapels, R. G. Driggers, D. Deaver, S. K. Moyer, and J. Palmer, “Midwave infrared and visible sensor performance modeling: small craft identification discrimination criteria for maritime security,” Appl. Opt. 46, 7345-7353 (2007).
[CrossRef] [PubMed]

S. Moyer, J. Hixson, T. C. Edwards, and K. Krapels, “Probability of identification of small hand-held objects for electro-optic forward-looking infrared systems,” Opt. Eng. 45, 063201(2006).
[CrossRef]

Krapels, K. A.

S. K. Moyer, E. Flug, T. C. Edwards, K. A. Krapels, and J. Scarborough “Identification of handheld objects for electro-optic/FLIR applications,” Proc. SPIE 5407, 116-126 (2004).
[CrossRef]

Miller, B.

B. Miller, “Status of NVESD real-time imaging sensor simulation capability,” Proc. SPIE 5084, 170-177 (2005).
[CrossRef]

Moyer, S.

S. Moyer, J. Hixson, T. C. Edwards, and K. Krapels, “Probability of identification of small hand-held objects for electro-optic forward-looking infrared systems,” Opt. Eng. 45, 063201(2006).
[CrossRef]

S. Moyer and N. Devitt “Resolvable cycle criteria for identifying personnel based on clothing and armament variations,” Proc. SPIE 5784, 60-71 (2005).
[CrossRef]

Moyer, S. K.

K. Krapels, R. G. Driggers, D. Deaver, S. K. Moyer, and J. Palmer, “Midwave infrared and visible sensor performance modeling: small craft identification discrimination criteria for maritime security,” Appl. Opt. 46, 7345-7353 (2007).
[CrossRef] [PubMed]

S. K. Moyer, E. Flug, T. C. Edwards, K. A. Krapels, and J. Scarborough “Identification of handheld objects for electro-optic/FLIR applications,” Proc. SPIE 5407, 116-126 (2004).
[CrossRef]

Palmer, J.

Scarborough, J.

S. K. Moyer, E. Flug, T. C. Edwards, K. A. Krapels, and J. Scarborough “Identification of handheld objects for electro-optic/FLIR applications,” Proc. SPIE 5407, 116-126 (2004).
[CrossRef]

Vollmerhausen, R.

R. Vollmerhausen and E. Jacobs “The targeting task performance (TTP) metric: a new model for predicting target acquisition performance,” U.S. Army CERDEC, Fort Belvoir, Va., Technical Report AMSEL-NV-TR-230, pp. 18-42, 47-51(2006).

Appl. Opt. (1)

Opt. Eng. (1)

S. Moyer, J. Hixson, T. C. Edwards, and K. Krapels, “Probability of identification of small hand-held objects for electro-optic forward-looking infrared systems,” Opt. Eng. 45, 063201(2006).
[CrossRef]

Proc. SPIE (3)

S. K. Moyer, E. Flug, T. C. Edwards, K. A. Krapels, and J. Scarborough “Identification of handheld objects for electro-optic/FLIR applications,” Proc. SPIE 5407, 116-126 (2004).
[CrossRef]

S. Moyer and N. Devitt “Resolvable cycle criteria for identifying personnel based on clothing and armament variations,” Proc. SPIE 5784, 60-71 (2005).
[CrossRef]

B. Miller, “Status of NVESD real-time imaging sensor simulation capability,” Proc. SPIE 5084, 170-177 (2005).
[CrossRef]

Other (6)

U.S. Army Research Development and Engineering Command, Communications and Electronics Research Development and Engineering Center, Night Vision and Electronics Sensors Directorate (NVESD).

U.S. Navy Office of Naval Research (ONR).

Night Vision Thermal and Image Processing (NVThermIP) Model Users Manual, Rev. 9, U.S. Army RDECOM, CERDEC, Night Vision and Electronic Sensors Directorate (2006).

J. W. Goodman, Introduction to Fourier Optics, 2nd ed. (McGraw-Hill , 1996), pp. 4-22.

R. Vollmerhausen and E. Jacobs “The targeting task performance (TTP) metric: a new model for predicting target acquisition performance,” U.S. Army CERDEC, Fort Belvoir, Va., Technical Report AMSEL-NV-TR-230, pp. 18-42, 47-51(2006).

L-3 Communications Avenger FLIR information retrieved from http://www.cinele.com/pdfs/Avenger.pdf, 13 Oct. 2008.

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Figures (16)

Fig. 1
Fig. 1

System CTF and apparent target contrast.

Fig. 2
Fig. 2

Key images of (a) a person crabbing and (b) a person picking up an object.

Fig. 3
Fig. 3

Perception experiment interface.

Fig. 4
Fig. 4

Activities included in experiment 1.

Fig. 5
Fig. 5

Static and dynamic probability of ID for 12 ground-based activities.

Fig. 6
Fig. 6

(a) Original image, (b) hand and object mask, (c) full body mask.

Fig. 7
Fig. 7

TTPF metric fit and data for static and dynamic tests using (a) hand and object target metric and (b) full body target metric.

Fig. 8
Fig. 8

Day and night probability of ID for 24 ground-based activities.

Fig. 9
Fig. 9

TTPF metric fit and data for MWIR day and night tests using (a) hand and object target metric and (b) full body target metric.

Fig. 10
Fig. 10

TTPF metric fit and data for visible band day using full body target metric.

Fig. 11
Fig. 11

Perception experiment interface for group activities.

Fig. 12
Fig. 12

Dynamic probability of ID as a function of blur level for group activities.

Fig. 13
Fig. 13

Comparison of TTPF metric fit and results for group and single-human activity experiments.

Fig. 14
Fig. 14

Example imagery of maritime activities showing (a) an actor baiting a line on the Manta, and (b) an actor holding a rifle on the Boston Whaler.

Fig. 15
Fig. 15

Dynamic probability of ID for maritime activities.

Fig. 16
Fig. 16

TTPF metric fit and data for maritime activities.

Tables (10)

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Table 1 Data Collection Sensor Specifications

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Table 2 Gaussian Blur Levels Applied in Experiment 1

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Table 3 Model Parameters for 12-Activity Target Set (Experiment 1)

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Table 4 List of Activities for Experiment 2

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Table 5 Model Parameters for 24-Activity Dynamic Target Set (Experiment 2)

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Table 6 Gaussian Blur Levels Applied in Experiment 3

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Table 7 Modeling Parameters Derived from Group-Activity and Individual-Activity Experiments

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Table 8 List of Activities for Maritime Environment

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Table 9 Model Parameters for Maritime Human Activities (Experiment 4)

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Table 10 Summary of Model Calibration Parameters for Human Activity Discrimination

Equations (12)

Equations on this page are rendered with MathJax. Learn more.

CTF system CTF eye MTF sensor .
S = A projected .
ϕ = S / R ,
RSS Δ T = ( T tgt T Bkg ) 2 + σ tgt 2 ,
C = RSS Δ T 2 μ scene ,
TTP = ξ low ξ high C apparent CTF system ξ .
V = TTP × ϕ .
P ID ( V ) = ( V / V 50 ) β 1 + ( V / V 50 ) β ,
f ( x , b ) = 1 s e π ( x / b ) 2 ,
I exp ( x , b ) = I orig ( x ) * * f ( x , b ) ,
P Corrected = P ID P Chance P Expert P Chance .
Confidence Interval = mean ± 1.96 ( σ P ID number of observers ) .

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