University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2007 Tamara Munzner Vision/Color Week 5, Mon.

Slides:



Advertisements
Similar presentations
University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2010 Tamara Munzner Vision/Color Week 5, Fri.
Advertisements

CS 445 / 645 Introduction to Computer Graphics Lecture 13 Color Color.
Introduction to Computer Graphics ColorColor. Specifying Color Color perception usually involves three quantities: Hue: Distinguishes between colors like.
Color To understand how to make realistic images, we need a basic understanding of the physics and physiology of vision.
Achromatic and Colored Light CS 288 9/17/1998 Vic.
Light Light is fundamental for color vision Unless there is a source of light, there is nothing to see! What do we see? We do not see objects, but the.
University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2005 Tamara Munzner Color Week 5, Fri Feb.
University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2008 Tamara Munzner Viewing/Projections IV.
Why is this hard to read. Unrelated vs. Related Color Unrelated color: color perceived to belong to an area in isolation (CIE 17.4) Related color: color.
University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2005 Tamara Munzner Projections II Week 4,
University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2007 Tamara Munzner Viewing/Projections III.
University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2007 Tamara Munzner Vision/Color II, Virtual.
School of Computing Science Simon Fraser University
CS 4731: Computer Graphics Lecture 24: Color Science
University of British Columbia CPSC 414 Computer Graphics © Tamara Munzner 1 Color Week 10, Wed 5 Nov 2003.
SWE 423: Multimedia Systems Chapter 4: Graphics and Images (2)
© 2002 by Yu Hen Hu 1 ECE533 Digital Image Processing Color Imaging.
University of British Columbia CPSC 414 Computer Graphics © Tamara Munzner 1 Color 2 Week 10, Fri 7 Nov 2003.
Trichromacy Helmholtz thought three separate images went forward, R, G, B. Wrong because retinal processing combines them in opponent channels. Hering.
COLOR and the human response to light
Display Issues Ed Angel Professor of Computer Science, Electrical and Computer Engineering, and Media Arts University of New Mexico.
University of British Columbia CPSC 414 Computer Graphics © Tamara Munzner 1 Viewing and Projections Mon 22 Sep 2003 project 1 solution demo recap: projections.
1 CSCE441: Computer Graphics: Color Models Jinxiang Chai.
Color Models AM Radio FM Radio + TV Microwave Infrared Ultraviolet Visible.
9/14/04© University of Wisconsin, CS559 Spring 2004 Last Time Intensity perception – the importance of ratios Dynamic Range – what it means and some of.
Course Website: Digital Image Processing Colour Image Processing.
Digital Image Processing Colour Image Processing.
CS 376 Introduction to Computer Graphics 01 / 26 / 2007 Instructor: Michael Eckmann.
Any questions about the current assignment? (I’ll do my best to help!)
1 Color vision and representation S M L.
COLLEGE OF ENGINEERING UNIVERSITY OF PORTO COMPUTER GRAPHICS AND INTERFACES / GRAPHICS SYSTEMS JGB / AAS Light and Color Graphics Systems / Computer.
Chapter 3: Colorimetry How to measure or specify color? Color dictionary?
CS 445 / 645: Introductory Computer Graphics Color.
Color. Contents Light and color The visible light spectrum Primary and secondary colors Color spaces –RGB, CMY, YIQ, HLS, CIE –CIE XYZ, CIE xyY and CIE.
CS 445 / 645 Introduction to Computer Graphics Lecture 13 Color Color.
Color 2011, Fall. Colorimetry : Definition (1/2) Colorimetry  Light is perceived in the visible band from 380 to 780 nm  distribution of wavelengths.
Color Theory ‣ What is color? ‣ How do we perceive it? ‣ How do we describe and match colors? ‣ Color spaces.
1 Introduction to Computer Graphics with WebGL Ed Angel Professor Emeritus of Computer Science Founding Director, Arts, Research, Technology and Science.
CSC361/ Digital Media Burg/Wong
CS6825: Color 2 Light and Color Light is electromagnetic radiation Light is electromagnetic radiation Visible light: nm. range Visible light:
Graphics Lecture 4: Slide 1 Interactive Computer Graphics Lecture 4: Colour.
CS 551 / 645: Introductory Computer Graphics Color.
University of British Columbia CPSC 314 Computer Graphics May-June 2005 Tamara Munzner Rasterization, Interpolation,
Three-Receptor Model Designing a system that can individually display thousands of colors is very difficult Instead, colors can be reproduced by mixing.
University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2008 Tamara Munzner Color II, Lighting/Shading.
1 CSCE441: Computer Graphics: Color Models Jinxiang Chai.
Introduction to Computer Graphics
EEL Introduction to Computer Graphics PPT12: Color models Yamini Bura – U
Color Models. Color models,cont’d Different meanings of color: painting wavelength of visible light human eye perception.
Greg Humphreys CS445: Intro Graphics University of Virginia, Fall 2003 Raster Graphics and Color Greg Humphreys University of Virginia CS 445, Fall 2003.
1 CSCE441: Computer Graphics: Color Models Jinxiang Chai.
University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2007 Tamara Munzner Viewing/Projections IV.
CS-321 Dr. Mark L. Hornick 1 Color Perception. CS-321 Dr. Mark L. Hornick 2 Color Perception.
David Luebke 1 2/5/2016 Color CS 445/645 Introduction to Computer Graphics David Luebke, Spring 2003.
David Luebke2/23/2016 CS 551 / 645: Introductory Computer Graphics Color Continued Clipping in 3D.
David Luebke3/11/2016 CS 551 / 645: Introductory Computer Graphics Geometric transforms: perspective projection Color.
Vision/Color II, Rasterization Week 6, Mon Feb 8
09/10/02(c) University of Wisconsin, CS559 Fall 2002 Last Time Digital Images –Spatial and Color resolution Color –The physics of color.
Color University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2016 Tamara Munzner.
Computer Graphics: Achromatic and Coloured Light.
1 of 32 Computer Graphics Color. 2 of 32 Basics Of Color elements of color:
Color Models Light property Color models.
Half Toning Dithering RGB CMYK Models
CS 551 / 645: Introductory Computer Graphics
COLOR space Mohiuddin Ahmad.
Pengenalan Warna Teori Warna.
Color Representation Although we can differentiate a hundred different grey-levels, we can easily differentiate thousands of colors.
Color Model By : Mustafa Salam.
Color Models l Ultraviolet Infrared 10 Microwave 10
Color Theory What is color? How do we perceive it?
Presentation transcript:

University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2007 Tamara Munzner Vision/Color Week 5, Mon Feb 5

2 Reading for Today RB Chap Color FCG Sections FCG Chap 20 Color FCG Chap 21 Visual Perception

3 Reading for Next Time

4 Project 1 Grading News don’t forget to show up 10 min before your slot see news item on top of course page for signup slot reminders signup snafu: Wed overlaps with class reschedule if possible

5 Midterm News midterm Friday Feb 9 closed book no calculators allowed to have one page of notes handwritten, one side of 8.5x11” sheet this room (DMP 301), 10-10:50 material covered transformations, viewing/projection

6 Review: N2D Transformation x y viewport NDC height width x y

7 x z NDCS y (-1,-1,-1) (1,1,1) x=left x=right y=top y=bottom z=-near z=-far x VCS y z Review: Perspective Derivation shear scale projection-normalization

8 Review: OpenGL Example glMatrixMode( GL_PROJECTION ); glLoadIdentity(); gluPerspective( 45, 1.0, 0.1, ); glMatrixMode( GL_MODELVIEW ); glLoadIdentity(); glTranslatef( 0.0, 0.0, -5.0 ); glPushMatrix() glTranslate( 4, 4, 0 ); glutSolidTeapot(1); glPopMatrix(); glTranslate( 2, 2, 0); glutSolidTeapot(1); OCS2 O2W VCSmodelingtransformationviewingtransformation projectiontransformation objectworld viewing W2VV2C WCS transformations that are applied first are specified last OCS1 WCS VCS W2O W2O CCS clipping CCS OCS

9 Review: Projection Taxonomy planarprojections perspective:1,2,3-point parallel oblique orthographic cabinet cavalier top,front,side axonometric:isometricdimetrictrimetric perspective: projectors converge orthographic, axonometric: projectors parallel and perpendicular to projection plane oblique: projectors parallel, but not perpendicular to projection plane

10 Vision/Color

11 RGB Color triple (r, g, b) represents colors with amount of red, green, and blue hardware-centric used by OpenGL

12 Alpha fourth component for transparency (r,g,b,  ) fraction we can see through c =  c f + (1-  )c b more on compositing later

13 Additive vs. Subtractive Colors additive: light monitors, LCDs RGB model subtractive: pigment printers CMY model dyes absorb light additive subtractive

14 Component Color component-wise multiplication of colors (a0,a1,a2) * (b0,b1,b2) = (a0*b0, a1*b1, a2*b2) why does this work? must dive into light, human vision, color spaces

15 Electromagnetic Spectrum

16 White Light sun or light bulbs emit all frequencies within visible range to produce what we perceive as "white light"

17 Sunlight Spectrum spectral distribution: power vs. wavelength

18 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 determines what we perceive as the color of the object

19 Hue hue (or simply, "color") is dominant wavelength/frequency integration of energy for all visible wavelengths is proportional to intensity of color

20 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 saturation: how far is color from grey pink is less saturated than red sky blue is less saturated than royal blue

21 Physiology of Vision the retina rods b/w, edges cones 3 types color sensors uneven distribution dense fovea

22 Foveal Vision hold out your thumb at arm’s length

23 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)

24 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 demo

25 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!

26 Negative Lobes exact target match with phosphors not possible possible: point red light to shine on target impossible: remove red from CRT phosphors 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

27 CIE Color Space CIE defined three “imaginary” lights X, Y, and Z, any wavelength can be matched perceptually by positive combinations Note that: X ~ R Y ~ G Z ~ B

28 Measured vs. CIE Color Spaces measured basis monochromatic lights physical observations negative lobes transformed basis “imaginary” lights all positive, unit area Y is luminance, no hue X,Z no luminance

29 CIE and Chromaticity Diagram X, Y, Z form 3D shape project X, Y, Z on X+Y+Z=1 plane for 2D color space separate color from brightness chromaticity diagram x = X / (X+Y+Z) y = Y / (X+Y+Z)

30 Device Color Gamuts gamut is polygon, device primaries at corners defines reproducible color range X, Y, and Z are hypothetical light sources, no device can produce entire gamut

31 Display Gamuts From A Field Guide to Digital Color, © A.K. Peters, 2003

32 Projector Gamuts From A Field Guide to Digital Color, © A.K. Peters, 2003

33 RGB Color Space (Color Cube) define colors with (r, g, b) amounts of red, green, and blue used by OpenGL hardware-centric RGB color cube sits within CIE color space subset of perceivable colors scale, rotate, shear cube

34 HSV Color Space more intuitive color space for people H = Hue S = Saturation V = Value or brightness B or intensity I or lightness L Value Saturation Hue

35 HSV and RGB HSV/HSI conversion from RGB not expressible in matrix

36 YIQ Color Space color model used for color TV Y is luminance (same as CIE) I & Q are color (not same I as HSI!) using Y backwards compatible for B/W TVs conversion from RGB is linear green is much lighter than red, and red lighter than blue Q I

37 Luminance vs. Intensity luminance Y of YIQ 0.299R G B intensity/brightness I/V/B of HSI/HSV/HSB 0.333R G B

38 Opponent Color definition achromatic axis R-G and Y-B axis separate lightness from chroma channels first level encoding linear combination of LMS before optic nerve basis for perception defines “color blindness”

39 vischeck.com simulates color vision deficiencies DeuteranopeProtanopeTritanope Normal vision

40 Adaptation, Surrounding Color color perception is also affected by adaptation (move from sunlight to dark room) surrounding color/intensity: simultaneous contrast effect

41 Color/Lightness Constancy Image courtesy of John McCann

42 Color/Lightness Constancy Image courtesy of John McCann

43 Color Constancy automatic “white balance” from change in illumination vast amount of processing behind the scenes! colorimetry vs. perception

44 Stroop Effect red blue orange purple green

45 Stroop Effect blue green purple red orange interplay between cognition and perception