university of british columbia cpsc 314 computer graphics jan-apr 2005 tamara munzner cs314/vjan2005...
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University of British ColumbiaCPSC 314 Computer Graphics
Jan-Apr 2005
Tamara Munzner
http://www.ugrad.cs.ubc.ca/~cs314/Vjan2005
Color
Week 5, Fri Feb 4
2
Review: Shading Models
flat shading compute Phong lighting once for entire
polygon Gouraud shading
compute Phong lighting at the vertices and interpolate lighting values across polygon
Phong shading compute averaged vertex normals interpolate normals across polygon and
perform Phong lighting across polygon
3
Correction: Phong Shading
linearly interpolating surface normal across the facet, applying Phong lighting model at every pixel same input as Gouraud shading pro: much smoother results con: considerably more expensive
not the same as Phong lighting common confusion Phong lighting: empirical model to calculate
illumination at a point on a surface
4
Review/Correction: Non-Photorealism
draw silhouettes and creases cool-to-warm shading
http://www.cs.utah.edu/~gooch/SIG98/paper/drawing.html
€
(n0 ⋅n1 ) ≤ threshold
5
Computing Normals per-vertex normals by interpolating per-facet
normals OpenGL supports both
computing normal for a polygon
c
b
a
6
Computing Normals per-vertex normals by interpolating per-facet
normals OpenGL supports both
computing normal for a polygon three points form two vectors
c
b
a
b-c
a-b
7
Computing Normals per-vertex normals by interpolating per-facet
normals OpenGL supports both
computing normal for a polygon three points form two vectors cross: normal of plane
c
b
a
b-c
a-b
(a-b) x (b-c)
8
Computing Normals per-vertex normals by interpolating per-facet
normals OpenGL supports both
computing normal for a polygon three points form two vectors cross: normal of plane
which side of plane is up? counterclockwise
point order convention
c
b
a
b-c
a-b
(a-b) x (b-c)
University of British ColumbiaCPSC 314 Computer Graphics
Jan-Apr 2005
Tamara Munzner
Color
10
Basics Of Color
elements of color:
11
Basics of Color
Physics: Illumination
Electromagnetic spectra Reflection
Material properties Surface geometry and microgeometry (i.e.,
polished versus matte versus brushed) Perception
Physiology and neurophysiology Perceptual psychology
12
Electromagnetic Spectrum
13
White Light
Sun or light bulbs emit all frequencies within the visible range to produce what we perceive as the "white light"
14
Sunlight Spectrum
15
White Light and Color
when white light is incident upon an object, some frequencies are reflected and some are absorbed by the object
combination of frequencies present in the reflected light that determinses what we perceive as the color of the object
16
Hue
hue (or simply, "color") is dominant wavelength
integration of energy for all visible wavelengths is proportional to intensity of color
17
Saturation or Purity of Light
how washed out or how pure the color of the light appears contribution of dominant light vs. other
frequencies producing white light
18
Intensity vs. Brightness
intensity : radiant energy emitted per unit of time, per unit solid angle, and per unit projected area of the source (related to the luminance of the source)
brightness : perceived intensity of light
19
Humans and Light when we view a source of light, our eyes respond
respond to hue: the color we see (red, green, purple)
dominant frequency saturation: how far is color from grey
(pink is less saturated than red, sky blue is less saturated than royal blue)
brightness: how bright is the color how close is the color to white or black how bright are the lights illuminating the object?
20
Physiology of Vision
the eye: the retina
rods cones
color!
21
Physiology of Vision
center of retina is densely packed region called the fovea. cones much denser here than the periphery
22
Trichromacy three types of cones
L or R, most sensitive to red light (610 nm) M or G, most sensitive to green light (560 nm) S or B, most sensitive to blue light (430 nm)
color blindness results from missing cone type(s)
23
Metamers a given perceptual sensation of color derives from the stimulus of all three cone types
identical perceptions of color can thus be caused by very different spectra
24
Metamer Demo http://www.cs.brown.edu/exploratories/freeSoftware/catalogs/color_theory.html
25
Adaptation, Surrounding Color
color perception is also affected by adaptation (move from sunlight to dark room) surrounding color/intensity:
simultaneous contrast effect
26
Bezold Effect
impact of outlines
27
Color Constancy
28
Color Constancy
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Color Constancy
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Color Constancy
31
Color Constancy
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Color Constancy
33
Color Constancy
automatic “white balance” from change in illumination
vast amount of processing behind the scenes!
colorimetry vs. perception
34
Color Spaces
three types of cones suggests color is a 3D quantity. how to define 3D color space?
idea: perceptually based measurement shine given wavelength () on a screen user must control three pure lights producing
three other wavelengths (say R=700nm, G=546nm, and B=436nm)
adjust intensity of RGB until colors are identical this works because of metamers!
35
Negative Lobes
exact target match with phosphors not possible
some red had to be added to target color to permit exact match using “knobs” on RGB intensity output of CRT
equivalently (theoretically), some red could have been removed from CRT output
figure shows that red phosphor must remove some cyan for perfect match
CRT phosphors cannot remove cyan, so 500 nm cannot be generated
36
Negative Lobes
can’t generate all other wavelenths with any set of three positive monochromatic lights!
solution: convert to new synthetic coordinate system to make the job easy
37
CIE Color Space
CIE defined three “imaginary” lights X, Y, and Z, any wavelength can be matched perceptually by positive combinations
Note that:X ~ RY ~ GZ ~ B
38
Measured vs. CIE Color Spaces
measured basis monochromatic lights physical observations negative lobes
transformed basis “imaginary” lights all positive, unit area Y is luminance
39
CIE Color Space Gamut
the gamut of all colors perceivable is thus a three-dimensional shape in X,Y,Z
color = X’X + Y’Y + Z’Z
40
RGB Color Space (Color Cube) define colors with (r, g, b)
amounts of red, green, and blue used by OpenGL
RGB color cube sits within CIE color space something like this subset of perceivable colors
41
CIE Chromaticity Diagram (1931)
For simplicity, we often project to the 2D plane X’+Y’+Z’=1
X’ = X’ / (X’+Y’+Z’)Y’ = Y’ / (X’+Y’+Z’)Z’ = 1 – X’ – Y’
42
Device Color Gamuts
use CIE chromaticity diagram to compare the gamuts of various devices
43
Device Color Gamuts
Since X, Y, and Z are hypothetical light sources, no real device can produce the entire gamut of perceivable color
Example: CRT monitor
44
Gamut Mapping
45
YIQ Color Space
YIQ is the color model used for color TV in America. Y is brightness, I & Q are color note: Y is the same as CIE’s Y result: use the Y alone and backwards
compatibility with B/W TV!
46
Converting Color Spaces
converting between color models can also be expressed as a matrix transform
note the relative unimportance of blue in computing the Y
⎥⎥⎥
⎦
⎤
⎢⎢⎢
⎣
⎡
⎥⎥⎥
⎦
⎤
⎢⎢⎢
⎣
⎡
−−−=
⎥⎥⎥
⎦
⎤
⎢⎢⎢
⎣
⎡
B
G
R
Q
I
Y
31.052.021.0
32.028.060.0
11.059.030.0
47
HSV Color Space
a more intuitive color space H = Hue S = Saturation V = Value (or brightness)
ValueSaturation
Hue
48
Simple Model of Color
based on RGB triples surface interactions also simplified
49
50
The Gamma Problem
device gamma
monitor: I= A(k1D+k2V)
typical monitor =2.5 LCD: nearly linear
OS gamma defined by operating system
inverse gamma curve I1/
“gamma correction”
51
Display System Gamma
product of device and OS curves divide device by OS gammaDS D OS
display system gamma varies different devices, different OS nonlinear
viewing conditions also affect perception of “gamma”
PC Mac SGI
1.0 1.4 1.7
Default OS Gamma
PC Mac SGI
2.2 1.6 1.3
Default DS Gamma
52
Intensity Mapping