Information Technology

Robust Background Subtraction Based on
Perceptual Mixture-of-Gaussians with
Dynamic Adaptation Spe...
Agenda
 Background Subtraction
 Statistical Background Subtraction
 Perception Inspired Background Subtraction

 Dynam...
Background Subtraction
Input

Output

Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed

December 30, 2013

3
Background Subtraction: Challenges
Basic Background Subtraction (e.g., BBS)
-

Current frame

Challenges

=

Background

F...
Statistical Background Subtraction
ω1

ω2

ω3

σ12

σ22

σ32

µ1

µ2

µ3

road

car

shadow

65%

20%

Statistical Approac...
Perception Inspired Background Subtraction
x = c2 b

Current
Frame

Detection with
Low x

Detection with
High x

x

x
P(x)...
Weber’s Law
How human visual system perceives noticeable intensity
deviation from the background?

Ernst Weber, an experim...
Weber’s Law
Ernst Weber, an experimental psychologist in the
19th century, observed that the just-noticeable
increment ΔI ...
Perceptual tolerance of HVS
What is the perceptual tolerance level in distinguishing
distorted intensity measures?

p dB

...
Our Problem: c2 = ?
x = c2 b
x

x
P(x)

Weber’s Law

x = c2b
Perceptual Threshold, TP (0.5 dB)

 255
20 log10 
 bx


...
Linear Relationship

x

b
Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed

December 30, 2013

11
Rod and Cone
 Rods and Cones are two different types of
photoreceptor cells in the retina of human eye
 Rods

– Operate ...
Error Sensitivity in Darker Background

Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed

December 30, 2013

...
Piece-wise Liner Relationship

Scotopic Vision (R)

Photopic Vision (C)
Te
Perceptual Mixture-of-Gaussians with Dynamic Ad...
Dynamic Adaptation Speed
•Sleeping person problem
•Walking person problem

Perceptual Mixture-of-Gaussians with Dynamic Ad...
Dynamic Adaptation Speed

Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed

December 30, 2013

16
Dynamic Adaptation Speed

Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed

December 30, 2013

17
Dynamic Adaptation Speed

Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed

December 30, 2013

18
Experiments
Test Sequences
 Total 50 test sequences from 8 different sources
 Scenario distribution






Indoor
Ou...
Test Sequences

PETS (9) Wallflower (7) UCF (7)

IBM (11)

CAVIAR (7)

Te

VSSN06 (7)

Perceptual Mixture-of-Gaussians wit...
Experiments

Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed

December 30, 2013

21
Experiments

Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed

December 30, 2013

22
Experiments

Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed

December 30, 2013

23
First
Frame

Test
Frame

Ground
Truth

MOG
(S&G)

MOG
(Lee)

ViBe

Perceptual Mixture-of-Gaussians with Dynamic Adaptation...
Summary
 Realistic background value prediction: high model agility
and superior detection quality at fast learning rate.
...
Q&A

Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed

December 30, 2013

26
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Talk 2012-icmew-perception

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Talk 2012-icmew-perception

  1. 1. Information Technology Robust Background Subtraction Based on Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed Mahfuzul Haque and Manzur Murshed
  2. 2. Agenda  Background Subtraction  Statistical Background Subtraction  Perception Inspired Background Subtraction  Dynamic Adaptation Speed  Experiments  Summary  Q&A Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 2
  3. 3. Background Subtraction Input Output Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 3
  4. 4. Background Subtraction: Challenges Basic Background Subtraction (e.g., BBS) - Current frame Challenges = Background Foreground Blob Dynamic Background Subtraction(e.g., MOG) Background     Illumination variation Local background motion Camera displacement Shadow and reflection Model Current frame Foreground Blob Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 4
  5. 5. Statistical Background Subtraction ω1 ω2 ω3 σ12 σ22 σ32 µ1 µ2 µ3 road car shadow 65% 20% Statistical Approaches x x P(x) Our Hypothesis (Perception Inspired) x BBS: x = c MOG: x = c1σ μ 15% x x = c2b P(x) Te b Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 5
  6. 6. Perception Inspired Background Subtraction x = c2 b Current Frame Detection with Low x Detection with High x x x P(x) b Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 6
  7. 7. Weber’s Law How human visual system perceives noticeable intensity deviation from the background? Ernst Weber, an experimental psychologist in the 19th century, observed that the just-noticeable increment ΔI is linearly proportional to the background intensity I. ΔI = c2I Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 7
  8. 8. Weber’s Law Ernst Weber, an experimental psychologist in the 19th century, observed that the just-noticeable increment ΔI is linearly proportional to the background intensity I. ? x x ΔI = c2I x x = c2 b P(x) b Te b Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 8
  9. 9. Perceptual tolerance of HVS What is the perceptual tolerance level in distinguishing distorted intensity measures? p dB Method 1 Reference q dB Method 2 Image Distorted Images |p – q| < 0.5 dB Not perceivable by human visual system Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 9
  10. 10. Our Problem: c2 = ? x = c2 b x x P(x) Weber’s Law x = c2b Perceptual Threshold, TP (0.5 dB)  255 20 log10   bx      20 log  255 10  b  x      1  2TP  b Te Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 10
  11. 11. Linear Relationship x b Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 11
  12. 12. Rod and Cone  Rods and Cones are two different types of photoreceptor cells in the retina of human eye  Rods – Operate in less intense light – Responsible for scotopic vision (night vision)  Cones – Operate in relatively bright light – Responsible for photopic (color vision) Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 12
  13. 13. Error Sensitivity in Darker Background Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 13
  14. 14. Piece-wise Liner Relationship Scotopic Vision (R) Photopic Vision (C) Te Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 14
  15. 15. Dynamic Adaptation Speed •Sleeping person problem •Walking person problem Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 15
  16. 16. Dynamic Adaptation Speed Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 16
  17. 17. Dynamic Adaptation Speed Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 17
  18. 18. Dynamic Adaptation Speed Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 18
  19. 19. Experiments Test Sequences  Total 50 test sequences from 8 different sources  Scenario distribution      Indoor Outdoor Multimodal Shadow and Reflection Low background-foreground contrast False Classification Evaluation  Qualitative and quantitative comparison:  MOG (S&G) (TPAMI, 2000) False Positive (FP) False Negative (FN)  MOG (Lee) (TPAMI, 2005)  ViBe (TIP, 2011) Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 19
  20. 20. Test Sequences PETS (9) Wallflower (7) UCF (7) IBM (11) CAVIAR (7) Te VSSN06 (7) Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed Other (2) December 30, 2013 20
  21. 21. Experiments Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 21
  22. 22. Experiments Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 22
  23. 23. Experiments Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 23
  24. 24. First Frame Test Frame Ground Truth MOG (S&G) MOG (Lee) ViBe Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed Proposed December 30, 2013 24
  25. 25. Summary  Realistic background value prediction: high model agility and superior detection quality at fast learning rate.  No context related information: high stability across changing scenarios.  Perception based detection threshold: superior detection quality in terms of shadow, noise, and reflection.  Perceptual model similarity: optimal number of models throughout the system life cycle.  Parameter-less background subtraction: ideal for realtime video analytics. Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 25
  26. 26. Q&A Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed December 30, 2013 26

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