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Computer VisionComputer Vision
Computer Engineering Sejong UniversityComputer Engineering, Sejong University
Dongil HanDongil Han
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Chapter 1: Cameras
Lens Human Eye Human Eye Image sensorg
Optical Engineering Sejong UniversityOptical Engineering, Sejong UniversityYouSeok Kim
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Lens
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P ti P j ti i h l ti
Lens
Perspective Projection : pinhole perspective
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Lens
P ti P j ti i h l tiPerspective Projection : pinhole perspective
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Lens
P ti P j ti i h l tiPerspective Projection : pinhole perspective
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Affi P j ti k ti
Lens
Affine Projection : weak-perspective
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Lens
Affi P j ti th hi j tiAffine Projection : orthographic projection
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S h i l P j ti
Lens
Spherical Projection
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C ith l
Lens
Camera with lenses
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Lens
C ith l S ll lCamera with lens : Snells law
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Fi t d G t i O ti
Lens
First-order Geometric Optics
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Thi L G t
Lens
Thin Lenses : Geometry
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Thi L G t
Lens
Thin Lenses : Geometry
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Thi L G t
Lens
Thin Lenses : Geometry
Thin lens equation
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D th f fil d
Lens
Depth of filed
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Fil d f i
Lens
Filed of view
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Lens
Real Lens
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Ab ti
Lens
Aberration
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Ab ti S h i l b ti
Lens
Aberration-Spherical aberration
20/67http://blog.naver.com/ulisaram
Ab ti b ti
Lens
Aberration-coma aberration
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Ab ti A ti ti
Lens
Aberration-Astigmatism
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Ab ti fil d t
Lens
Aberration-filed curvature
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Ab ti Di t ti
Lens
Aberration-Distortion
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Ab ti Ch ti b ti
Lens
Aberration-Chromatic aberration
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Vi tti
Lens
Vignetting
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R l L
Lens
Real Lens
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Human Eye
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Human Eye
Structure of the human eye
Cornea :
Pupil :
Iris :
Lens : Blind
Retina :
Fovea :
Spot
Fovea :
Blind Spot :
O ti N Optic Nerve :
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R d d C
Human Eye
Rods
Rods and Cones
- respond to dim light for BW vision- respond to form and movement- do not contribute color vision
Cones- provide daylight color visionprovide daylight color vision- one of 3 spectral types: S(blue), M(green), L(red)- concentrated in the center of retina
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Human Eye
Human Eye
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h i
Human Eye
The Human Perception
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Human Eye
h d d C i l lThe Rod and Cone signal example
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Human Eye
Image Formation in the Eye
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B i ht Ad t ti
Human Eye
Brightness Adaptation
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B i ht Di i i ti
Human Eye
Brightness Discrimination
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P i d B i ht
Human Eye
Perceived Brightness
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Human Eye
Simultaneous Contrast
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O ti l ill i
Human Eye
Optical illusions
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Human Eye
1. 3 DD /
DD
1. 1. (vergence)2. (binocular disparity)
D
2. 1. (accomodation)
2. (motion parallax)3. (visual field size)4. (aerial perspective)5 (li ti )5. (linear perspective)6. (texture gradient)
3 /Takehiro Izumi /NHK
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3 , /Takehiro Izumi, /NHK , /, (1995)
Image sensor
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I i iti i i l
Image sensor
Image acquisition using a single sensor
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I i iti i li
Image sensor
Image acquisition using a line sensor
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I S i
Image sensor
Image Sensing
I i i Incoming energy is transformed into voltage.
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I i iti i
Image sensor
Image acquisition using a array sensor
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I f ti d l
Image sensor
Image formation model
- Creating a Digital Image
For computer processing, an image intensity function f(x,y) must be digitized both spatially and in amplitude. And f(x,y) must be non-zero and finitefinite.
0 < f(x,y)