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S1 Corporation, Korea. A Pixel-Weighting Method for Discriminating Objects of Different Sizes in an Image Captured from a Single Camera. Mookyung Park, Namsu Moon, Sangrim Ryu, Jeongpyo Kong, Yongjin Lee and Wangjin Mun. Alarm signal. Customer site. Instruction. Visit.

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slide1

S1 Corporation, Korea

A Pixel-Weighting Method for Discriminating Objects of Different Sizes in an Image Captured from a Single Camera

Mookyung Park, Namsu Moon, Sangrim Ryu,

Jeongpyo Kong, Yongjin Lee and Wangjin Mun

security service flow

Alarm signal

Customer site

Instruction

Visit

Centralized control office

Security Service Flow

Security agent

Cost∝ Number of visits

objectives

PIR sensor

( Passive Infra-Red )

Lacks intelligence

False alarm

Cost ↑

Vision sensor + Image processing

More Intelligence

Stereo : expensive

Single : cost-effective

Objectives

Single : cost-effective

Object size

 useful feature for discriminating objects

This talk is on a method of how to calculate the size of objects in an image captured from a single camera

objects in the images

Object

< Surveillance space >

< Surveillance space >

A

B

C

C

C

B

B

A

A

< Image >

< Image >

Objects in the images

Object

Proper weight of pixel

 Real size of objects

A

B

C

overview of calculation

Hx,y

Vy

Hx,y-1

trapezoid

pixel(x,y)

< Surveillance space >

< Surveillance space >

< Image >

< Surveillance space >

< Surveillance space >

Overview of Calculation
assumptions

1st.

The object is standing perpendicularly to the ground and is not floating in the air.

2nd.

The camera is installed at high location looking down objects like humans.

3rd.

The camera kept in a horizontal position, not tilting to the right of the left.

4th.

The effect of radial distortion of lens does not appear in the image.

Assumptions
parameters required

W2

W2

W2

W2

W2

W2

2

2

1

1

1

1

2

2

3

3

Blind zone

AVH

AVH

H

AV

AV

< Top view of the surveillance space >

H-1

AB

AB

he

he

Blind zone

Blind zone

1

2

1

2

3

3

AH

2

AHW

AHW

1

Blind zone

Blind zone

1

1

2

2

3

3

H-1

H-1

H

H

< Top view of the surveillance space >

< Top view of the surveillance space >

< Side view of the surveillance space >

Parameters Required

Even symmetry

Vertical angle of view

< Parameters >

Blind zone angle

Height of Installation

Vertical pixel number

H

AH

Horizontal angle of view

Horizontal pixel number

W

< Image >

< Side view of the surveillance space >

a x y v y h x y h x y 1

H

12

y

X

AVH

AVH

H

2

AV

1

W

AB

< Image >

he

θy

vy

Ly

Ly-1

θy

θy

Ax,y = ×Vy× ( Hx,y + Hx,y-1)

y

ybottom

Cy

slide9

12

AH2

AHW

Cy

Cy

Cy

Cy

Cy

Cy

Cy

Cy

θy

he

Dx,y

Ly

Dx-1,y

Hx,y

< Image >

Vy

Hx,y-1

Ax,y = ×Vy× (Hx,y+Hx,y-1)

Pixel (x,y)

experimental verification
Experimental set-up

Current

image

Reference

image

Difference

Binarization

Labeling

Noise Filter

Weighting

Experimental Verification
experimental results 1
For the same object

with different locations

a

b

Distance

Pixels

Weight sum

a

2

234

5241

b

3

156

5574

c

c

4

108

5454

d

5

78

5306

d

e

6

62

5821

e

Experimental Results (1)
experimental results 2
For objects of different sizes

Human

Small animal

a

Pixels

Weight sum

Small

animal

Human

Small

animal

Human

b

a

88

88

2628

5761

b

56

186

2144

5682

c

35

339

2243

5919

c

Experimental Results (2)
summary
Summary

Operational cost caused by false alarms can be significantly suppressed by adopting intelligent vision-based sensors in our security service business

Considering cost-effectiveness, we proposed a method of calculating the size of the object in the image captured from single camera

The calculation of object size requires parameters which are obtained when installing the vision sensor (camera)

Experimental results show that the proposed method produces a useful feature for distinguishing objects of different sizes