Normals. In OpenGL the normal vector is part of the state Set by glnormal*()
|
|
- Willa Knight
- 6 years ago
- Views:
Transcription
1 Ray Tracig 1
2 Normals OpeG the ormal vector is part of the state Set by glnormal*() -glnormal3f(x, y, z); -glnormal3fv(p); Usually we wat to set the ormal to have uit legth so cosie calculatios are correct - egth ca be affected by trasformatios - Note that scalig does ot preserve legth -gleable(g_normaze) allows for autoormalizatio at a performace pealty 2
3 Normal for Triagle plae (p - p 0 ) = 0 p 2 = (p 2 - p 0 ) (p 1 - p 0 ) ormalize / p p 0 p 1 Note that right-had rule determies outward face 3
4 Polygoal Shadig Shade a polygoal mesh - flat shadig - iterpolative or Gouraud shadig - Phog shadig polygoal mesh 4
5 Flat Shadig (1/2) Costat shadig - flat polygo : costat - distat light source l: costat - distat viewer v: costat Oe shadig calculatio for each polygo OpeG glshademodel(g_fat); distat source ad viewer 5
6 Flat Shadig (2/2) Always be disappoitig for a smooth surface - lateral ihibitio huma visual system has a remarkable sesitivity - Mach bads perceive the icreases i brightess alog the edges flat shadig of polygoal mesh perceived ad actual itesities at a edge We eed smoother shadig techiques to avoid it!! 6
7 Polygo Normals Polygos have a sigle ormal - Shades at the vertices as computed by the Phog model ca be almost same - detical for a distat viewer (default) or if there is o specular compoet Cosider model of sphere Wat differet ormals at each vertex eve though this cocept is ot quite correct mathematically 7
8 Mesh Shadig The previous example is ot geeral because we kew the ormal at each vertex aalytically For polygoal models, Gouraud proposed we use the average of the ormals aroud a mesh vertex = ( )/
9 Gouraud Shadig OpeG glshademodel(g_smooth); Oe lightig calculatio for each vertex - biliearly iterpolate colors Vertex ormal could be defied through iterpolatio ormals ear iterior vertex 9
10 Smooth Shadig We ca set a ew ormal at each vertex Easy for sphere model - f cetered at origi = p Now smooth shadig works (color value iterpolatio iside the mesh) Note silhouette edge 10
11 Wireframe 11
12 Flat Shadig 12
13 Gouraud Shadig 13
14 Phog Shadig (1/2) May ot prevet the appearace of Mach bads What if polygoal mesh is too coarse to capture illumiatio effects i polygo iteriors? iterpolate ormals across each polygo Oe shadig calculatio for each pixel off-lie Compute vertex ormal at each poit 1 A B, 1 C D edge ormals iterpolatio of ormals 14
15 Phog Shadig (2/2) Wireframe Flat Gouraud Phog 15
16 Gouraud ad Phog Shadig Gouraud Shadig - Fid average ormal at each vertex (vertex ormals) - Apply modified Phog model at each vertex - terpolate vertex shades across each polygo Phog shadig - Fid vertex ormals - terpolate vertex ormals across edges - terpolate edge ormals across polygo - Apply modified Phog model at each fragmet 16
17 Compariso f the polygo mesh approximates surfaces with a high curvatures, Phog shadig may look smooth while Gouraud shadig may show edges Phog shadig requires much more work tha Gouraud shadig - Util recetly ot available i real time systems Both eed data structures to represet meshes so we ca obtai vertex ormals 17
18 Shadows Shadow terms tell which light sources are blocked - Cast ray towards each light source i - S i = 0 if ray is blocked, S i = 1 otherwise Shadow Term E A A ( D N V R S ) S 18
19
20
21
22
23
24
25
26
27
28 28 Ray Castig Trace primary rays from camera - Direct illumiatio from ublocked lights oly S D A A E S N ) R V (
29 29 Recursive Ray Tracig Also trace secodary rays from hit surfaces - Global illumiatio from mirror reflectio ad trasparecy T T R S S D A A E S N ) R V (
30 30 Mirror Reflectio Trace secodary ray i directio of mirror reflectio T T R S S D A A E S N ) R V ( Radiace for mirror reflectio ray
31 31 Trasparecy (1/2) Trace secodary ray i directio of refractio T T R S S D A A E S N ) R V ( Radiace for refractio ray
32 Trasparecy (2/2) Trasparecy coefficiet is fractio trasmitted - T = 1 if object is trasparet - T = 0 if object is opaque - 0 < T < 1 if object is traslucet Trasparecy Coefficiet E A A D N S V R S S R T T ( ) 32
33 33 Ray Tracig Extesio of ray castig - ook for the visible surface for each pixel - Cotiue to bouce the ray aroud the scee T T R S S D A A E S N ) R V (
34 Ray Tracig Global illumiatio - Shadows - Refractios - ter-object reflectios Highly realistic vs. computatio time Shadow Reflectace Trasparecy E A A D N S V R S S R T T ( ) 34
35 Radiosity Goal Simulate diffuse iter-object reflectios ad shadows for a scee cosistig of oly perfectly diffused surface i the closed space 35
36 Basic idea Radiosity - Treat every polygo as light source 36
37 Radiosity Advatages - Physically models shadows ad idirect diffuse illumiatio - depedet of ay viewpoit Equatio B i E i ρ i B j F ij B i = Radiosity of patch i E i = Emissio of patch i ρ i = Reflectivity of patch i F i = Form-factor betwee patches i ad j 37
38 Form Factors Defiitio - Fractio of eergy leavig patch j that arrives at patch i Computatio - Hemishere Project a patch oto uit hemisphere Divide the area of the patch o the hemisphere with the total area - Hemi-cube Project oto uit hemisphere Project oto Hemi-cube 38
39 Matrix Solutio Methods 1 iteratio 2 iteratios 24 iteratios 100 iteratios 39
Computer Graphics. Surface Rendering Methods. Content. Polygonal rendering. Global rendering. November 14, 2005
Computer Graphics urface Rederig Methods November 4, 2005 Cotet Polygoal rederig flat shadig Gouraud shadig Phog shadig Global rederig ray tracig radiosity Polygoal Rederig hadig a polygoal mesh flat or
More informationLighting and Shading. Outline. Raytracing Example. Global Illumination. Local Illumination. Radiosity Example
CSCI 480 Computer Graphics Lecture 9 Lightig ad Shadig Light Sources Phog Illumiatio Model Normal Vectors [Agel Ch. 6.1-6.4] February 13, 2013 Jerej Barbic Uiversity of Souther Califoria http://www-bcf.usc.edu/~jbarbic/cs480-s13/
More informationAssigning colour to pixels or fragments. Modelling Illumination. We shall see how it is done in a rasterization model. CS475/CS675 - Lecture 14
- Computer Graphics Assigig colour to pixels or fragmets. Modellig Illumiatio Illumiatio Model : The Phog Model For a sigle light source total illumiatio at ay poit is give by: ecture 14: I =k a I a k
More informationCOMP 558 lecture 6 Sept. 27, 2010
Radiometry We have discussed how light travels i straight lies through space. We would like to be able to talk about how bright differet light rays are. Imagie a thi cylidrical tube ad cosider the amout
More informationComputer Graphics. Shading. Page. Copyright Gotsman, Elber, Barequet, Karni, Sheffer Computer Science, Technion. The Physics
Comuter Grahics Illumiatio Models & The Physics 2 Local vs. Global Illumiatio Models Examle Local model direct ad local iteractio of each object with the light. Ambiet Diffuse Global model: iteractios
More informationOpenGL Illumination example. 2IV60 Computer graphics set 8: Illumination Models and Surface-Rendering Methods. Introduction 2.
OpeG Illumiatio example 2I60 Computer graphics set 8: Illumiatio Models ad Surface-ederig Methods Jack va Wijk TU/e Glfloat lightpos[] = {2.0, 0.0, 3.0, 0.0}; Glfloat whitecolor[] = {1.0, 1.0, 1.0, 1.0};
More informationWhy Do We Care About Lighting? Computer Graphics Lighting. The Surface Normal. Flat Shading (Per-face) Setting a Surface Normal in OpenGL
Lightig Why Do We Care About Lightig? Lightig dis-ambiguates 3D scees This work is licesed uder a Creative Commos Attributio-NoCommercial- NoDerivatives 4.0 Iteratioal Licese Mike Bailey mjb@cs.oregostate.edu
More informationLight and shading. Source: A. Efros
Light ad shadig Source: A. Efros Image formatio What determies the brightess of a image piel? Sesor characteristics Light source properties Eposure Surface shape ad orietatio Optics Surface reflectace
More informationRendering. Ray Tracing
CS475m - Compter Graphics Lectre 16 : 1 Rederig Drawig images o the compter scree. We hae see oe rederig method already. Isses: Visibility What parts of a scee are isible? Clippig Cllig (Backface ad Occlsio)
More information27 Refraction, Dispersion, Internal Reflection
Chapter 7 Refractio, Dispersio, Iteral Reflectio 7 Refractio, Dispersio, Iteral Reflectio Whe we talked about thi film iterferece, we said that whe light ecouters a smooth iterface betwee two trasparet
More informationTexture Mapping. Jian Huang. This set of slides references the ones used at Ohio State for instruction.
Texture Mappig Jia Huag This set of slides refereces the oes used at Ohio State for istructio. Ca you do this What Dreams May Come Texture Mappig Of course, oe ca model the exact micro-geometry + material
More informationEigenimages. Digital Image Processing: Bernd Girod, 2013 Stanford University -- Eigenimages 1
Eigeimages Uitary trasforms Karhue-Loève trasform ad eigeimages Sirovich ad Kirby method Eigefaces for geder recogitio Fisher liear discrimat aalysis Fisherimages ad varyig illumiatio Fisherfaces vs. eigefaces
More informationThe Nature of Light. Chapter 22. Geometric Optics Using a Ray Approximation. Ray Approximation
The Nature of Light Chapter Reflectio ad Refractio of Light Sectios: 5, 8 Problems: 6, 7, 4, 30, 34, 38 Particles of light are called photos Each photo has a particular eergy E = h ƒ h is Plack s costat
More informationLecture 7 7 Refraction and Snell s Law Reading Assignment: Read Kipnis Chapter 4 Refraction of Light, Section III, IV
Lecture 7 7 Refractio ad Sell s Law Readig Assigmet: Read Kipis Chapter 4 Refractio of Light, Sectio III, IV 7. History I Eglish-speakig coutries, the law of refractio is kow as Sell s Law, after the Dutch
More informationPractical Implementation at tri-ace
Physically Based Shadig Models i Film ad Game Productio: Practical Implemetatio at tri-ace 1. Itroductio Yoshiharu Gotada tri-ace, Ic. I this paper, we preset our practical examples of physically based
More informationAssignment 5; Due Friday, February 10
Assigmet 5; Due Friday, February 10 17.9b The set X is just two circles joied at a poit, ad the set X is a grid i the plae, without the iteriors of the small squares. The picture below shows that the iteriors
More informationMathematics and Art Activity - Basic Plane Tessellation with GeoGebra
1 Mathematics ad Art Activity - Basic Plae Tessellatio with GeoGebra Worksheet: Explorig Regular Edge-Edge Tessellatios of the Cartesia Plae ad the Mathematics behid it. Goal: To eable Maths educators
More informationChapter 18: Ray Optics Questions & Problems
Chapter 18: Ray Optics Questios & Problems c -1 2 1 1 1 h s θr= θi 1siθ 1 = 2si θ 2 = θ c = si ( ) + = m = = v s s f h s 1 Example 18.1 At high oo, the su is almost directly above (about 2.0 o from the
More informationPhysics 11b Lecture #19
Physics b Lecture #9 Geometrical Optics S&J Chapter 34, 35 What We Did Last Time Itesity (power/area) of EM waves is give by the Poytig vector See slide #5 of Lecture #8 for a summary EM waves are produced
More informationLenses and Imaging (Part I) Parabloid mirror: perfect focusing
Leses ad Imagig (Part I) eview: paraboloid reflector, focusig Why is imagig ecessary: Huyges priciple Spherical & parallel ray budles, poits at ifiity efractio at spherical surfaces (paraial approimatio)
More informationCOSC 1P03. Ch 7 Recursion. Introduction to Data Structures 8.1
COSC 1P03 Ch 7 Recursio Itroductio to Data Structures 8.1 COSC 1P03 Recursio Recursio I Mathematics factorial Fiboacci umbers defie ifiite set with fiite defiitio I Computer Sciece sytax rules fiite defiitio,
More informationEigenimages. Digital Image Processing: Bernd Girod, Stanford University -- Eigenimages 1
Eigeimages Uitary trasforms Karhue-Loève trasform ad eigeimages Sirovich ad Kirby method Eigefaces for geder recogitio Fisher liear discrimat aalysis Fisherimages ad varyig illumiatio Fisherfaces vs. eigefaces
More informationPattern Recognition Systems Lab 1 Least Mean Squares
Patter Recogitio Systems Lab 1 Least Mea Squares 1. Objectives This laboratory work itroduces the OpeCV-based framework used throughout the course. I this assigmet a lie is fitted to a set of poits usig
More informationCS Polygon Scan Conversion. Slide 1
CS 112 - Polygo Sca Coversio Slide 1 Polygo Classificatio Covex All iterior agles are less tha 180 degrees Cocave Iterior agles ca be greater tha 180 degrees Degeerate polygos If all vertices are colliear
More information1. Sketch a concave polygon and explain why it is both concave and a polygon. A polygon is a simple closed curve that is the union of line segments.
SOLUTIONS MATH / Fial Review Questios, F5. Sketch a cocave polygo ad explai why it is both cocave ad a polygo. A polygo is a simple closed curve that is the uio of lie segmets. A polygo is cocave if it
More informationThe isoperimetric problem on the hypercube
The isoperimetric problem o the hypercube Prepared by: Steve Butler November 2, 2005 1 The isoperimetric problem We will cosider the -dimesioal hypercube Q Recall that the hypercube Q is a graph whose
More informationLenses and Imaging (Part I)
Leses ad Imagig (Part I) Why is imagig ecessary: Huyge s priciple Spherical & parallel ray budles, poits at ifiity efractio at spherical surfaces (paraial approimatio) Optical power ad imagig coditio Matri
More informationChapter 3 Classification of FFT Processor Algorithms
Chapter Classificatio of FFT Processor Algorithms The computatioal complexity of the Discrete Fourier trasform (DFT) is very high. It requires () 2 complex multiplicatios ad () complex additios [5]. As
More informationEVALUATION OF TRIGONOMETRIC FUNCTIONS
EVALUATION OF TRIGONOMETRIC FUNCTIONS Whe first exposed to trigoometric fuctios i high school studets are expected to memorize the values of the trigoometric fuctios of sie cosie taget for the special
More informationNumerical Methods Lecture 6 - Curve Fitting Techniques
Numerical Methods Lecture 6 - Curve Fittig Techiques Topics motivatio iterpolatio liear regressio higher order polyomial form expoetial form Curve fittig - motivatio For root fidig, we used a give fuctio
More informationAberrations in Lens & Mirrors (Hecht 6.3)
Aberratios i Les & Mirrors (Hecht 6.3) Aberratios are failures to focus to a "poit" Both mirrors ad les suffer from these Some are failures of paraxial assumptio 3 5 θ θ si( θ ) = θ + L 3! 5! Paraxial
More informationComputational Geometry
Computatioal Geometry Chapter 4 Liear programmig Duality Smallest eclosig disk O the Ageda Liear Programmig Slides courtesy of Craig Gotsma 4. 4. Liear Programmig - Example Defie: (amout amout cosumed
More informationAlpha Individual Solutions MAΘ National Convention 2013
Alpha Idividual Solutios MAΘ Natioal Covetio 0 Aswers:. D. A. C 4. D 5. C 6. B 7. A 8. C 9. D 0. B. B. A. D 4. C 5. A 6. C 7. B 8. A 9. A 0. C. E. B. D 4. C 5. A 6. D 7. B 8. C 9. D 0. B TB. 570 TB. 5
More information. Perform a geometric (ray-optics) construction (i.e., draw in the rays on the diagram) to show where the final image is formed.
MASSACHUSETTS INSTITUTE of TECHNOLOGY Departmet of Electrical Egieerig ad Computer Sciece 6.161 Moder Optics Project Laboratory 6.637 Optical Sigals, Devices & Systems Problem Set No. 1 Geometric optics
More informationSection 7.2: Direction Fields and Euler s Methods
Sectio 7.: Directio ields ad Euler s Methods Practice HW from Stewart Tetbook ot to had i p. 5 # -3 9-3 odd or a give differetial equatio we wat to look at was to fid its solutio. I this chapter we will
More informationSpherical Mirrors. Types of spherical mirrors. Lecture convex mirror: the. geometrical center is on the. opposite side of the mirror as
Lecture 14-1 Spherical Mirrors Types of spherical mirrors covex mirror: the geometrical ceter is o the opposite side of the mirror as the object. cocave mirror: the geometrical ceter is o the same side
More informationWavelet Transform. CSE 490 G Introduction to Data Compression Winter Wavelet Transformed Barbara (Enhanced) Wavelet Transformed Barbara (Actual)
Wavelet Trasform CSE 49 G Itroductio to Data Compressio Witer 6 Wavelet Trasform Codig PACW Wavelet Trasform A family of atios that filters the data ito low resolutio data plus detail data high pass filter
More informationVision & Perception. Simple model: simple reflectance/illumination model. image: x(n 1,n 2 )=i(n 1,n 2 )r(n 1,n 2 ) 0 < r(n 1,n 2 ) < 1
Visio & Perceptio Simple model: simple reflectace/illumiatio model Eye illumiatio source i( 1, 2 ) image: x( 1, 2 )=i( 1, 2 )r( 1, 2 ) reflectace term r( 1, 2 ) where 0 < i( 1, 2 ) < 0 < r( 1, 2 ) < 1
More informationThe Graphs of Polynomial Functions
Sectio 4.3 The Graphs of Polyomial Fuctios Objective 1: Uderstadig the Defiitio of a Polyomial Fuctio Defiitio Polyomial Fuctio 1 2 The fuctio ax a 1x a 2x a1x a0 is a polyomial fuctio of degree where
More informationLenses and imaging. MIT 2.71/ /10/01 wk2-a-1
Leses ad imagig Huyges priciple ad why we eed imagig istrumets A simple imagig istrumet: the pihole camera Priciple of image formatio usig leses Quatifyig leses: paraial approimatio & matri approach Focusig
More informationMath Section 2.2 Polynomial Functions
Math 1330 - Sectio. Polyomial Fuctios Our objectives i workig with polyomial fuctios will be, first, to gather iformatio about the graph of the fuctio ad, secod, to use that iformatio to geerate a reasoably
More informationVisualization of Gauss-Bonnet Theorem
Visualizatio of Gauss-Boet Theorem Yoichi Maeda maeda@keyaki.cc.u-tokai.ac.jp Departmet of Mathematics Tokai Uiversity Japa Abstract: The sum of exteral agles of a polygo is always costat, π. There are
More informationINSCRIBED CIRCLE OF GENERAL SEMI-REGULAR POLYGON AND SOME OF ITS FEATURES
INTERNATIONAL JOURNAL OF GEOMETRY Vol. 2 (2013), No. 1, 5-22 INSCRIBED CIRCLE OF GENERAL SEMI-REGULAR POLYGON AND SOME OF ITS FEATURES NENAD U. STOJANOVIĆ Abstract. If above each side of a regular polygo
More informationOrientation. Orientation 10/28/15
Orietatio Orietatio We will defie orietatio to mea a object s istataeous rotatioal cofiguratio Thik of it as the rotatioal equivalet of positio 1 Represetig Positios Cartesia coordiates (x,y,z) are a easy
More informationApparent Depth. B' l'
REFRACTION by PLANE SURFACES Apparet Depth Suppose we have a object B i a medium of idex which is viewed from a medium of idex '. If '
More informationParabolic Path to a Best Best-Fit Line:
Studet Activity : Fidig the Least Squares Regressio Lie By Explorig the Relatioship betwee Slope ad Residuals Objective: How does oe determie a best best-fit lie for a set of data? Eyeballig it may be
More informationRecursive Procedures. How can you model the relationship between consecutive terms of a sequence?
6. Recursive Procedures I Sectio 6.1, you used fuctio otatio to write a explicit formula to determie the value of ay term i a Sometimes it is easier to calculate oe term i a sequece usig the previous terms.
More informationParametric curves. Reading. Parametric polynomial curves. Mathematical curve representation. Brian Curless CSE 457 Spring 2015
Readig Required: Agel 0.-0.3, 0.5., 0.6-0.7, 0.9 Parametric curves Bria Curless CSE 457 Sprig 05 Optioal Bartels, Beatty, ad Barsy. A Itroductio to Splies for use i Computer Graphics ad Geometric Modelig,
More informationComputer Graphics Hardware An Overview
Computer Graphics Hardware A Overview Graphics System Moitor Iput devices CPU/Memory GPU Raster Graphics System Raster: A array of picture elemets Based o raster-sca TV techology The scree (ad a picture)
More informationPropagation of light: rays versus wave fronts; geometrical and physical optics
Propagatio of light: rays versus wave frots; geometrical ad physical optics A ray is a imagiary lie alog the directio of propagatio of the light wave: this lie is perpedicular to the wave frot If descriptio
More information3D Model Retrieval Method Based on Sample Prediction
20 Iteratioal Coferece o Computer Commuicatio ad Maagemet Proc.of CSIT vol.5 (20) (20) IACSIT Press, Sigapore 3D Model Retrieval Method Based o Sample Predictio Qigche Zhag, Ya Tag* School of Computer
More informationEE 584 MACHINE VISION
METU EE 584 Lecture Notes by A.Aydi ALATAN 0 EE 584 MACHINE VISION Itroductio elatio with other areas Image Formatio & Sesig Projectios Brightess Leses Image Sesig METU EE 584 Lecture Notes by A.Aydi ALATAN
More informationCubic Polynomial Curves with a Shape Parameter
roceedigs of the th WSEAS Iteratioal Coferece o Robotics Cotrol ad Maufacturig Techology Hagzhou Chia April -8 00 (pp5-70) Cubic olyomial Curves with a Shape arameter MO GUOLIANG ZHAO YANAN Iformatio ad
More informationReading. Parametric curves. Mathematical curve representation. Curves before computers. Required: Angel , , , 11.9.
Readig Required: Agel.-.3,.5.,.6-.7,.9. Optioal Parametric curves Bartels, Beatty, ad Barsky. A Itroductio to Splies for use i Computer Graphics ad Geometric Modelig, 987. Fari. Curves ad Surfaces for
More informationLecture 18. Optimization in n dimensions
Lecture 8 Optimizatio i dimesios Itroductio We ow cosider the problem of miimizig a sigle scalar fuctio of variables, f x, where x=[ x, x,, x ]T. The D case ca be visualized as fidig the lowest poit of
More informationOctahedral Graph Scaling
Octahedral Graph Scalig Peter Russell Jauary 1, 2015 Abstract There is presetly o strog iterpretatio for the otio of -vertex graph scalig. This paper presets a ew defiitio for the term i the cotext of
More informationPanel Methods : Mini-Lecture. David Willis
Pael Methods : Mii-Lecture David Willis 3D - Pael Method Examples Other Applicatios of Pael Methods http://www.flowsol.co.uk/ http://oe.mit.edu/flowlab/ Boudary Elemet Methods Pael methods belog to a broader
More information9.1. Sequences and Series. Sequences. What you should learn. Why you should learn it. Definition of Sequence
_9.qxd // : AM Page Chapter 9 Sequeces, Series, ad Probability 9. Sequeces ad Series What you should lear Use sequece otatio to write the terms of sequeces. Use factorial otatio. Use summatio otatio to
More informationForce Network Analysis using Complementary Energy
orce Network Aalysis usig Complemetary Eergy Adrew BORGART Assistat Professor Delft Uiversity of Techology Delft, The Netherlads A.Borgart@tudelft.l Yaick LIEM Studet Delft Uiversity of Techology Delft,
More information游戏设计与开发. Outline. Game Programming Topics. Building A Game
1896 1935 1987 2006 Outlie 游戏设计与开发 Real Time Requiremet A Coceptual Rederig Pipelie The Graphics Processig Uit (GPU) Example 技术篇 : 实时图形硬件 Game Programmig Topics Focus: Buildig game ad virtual world High-level
More informationAP B mirrors and lenses websheet 23.2
Name: Class: _ Date: _ ID: A AP B mirrors ad leses websheet 232 Multiple Choice Idetify the choice that best completes the statemet or aswers the questio 1 The of light ca chage whe light is refracted
More informationOverview. Shading. Shading. Why we need shading. Shading Light-material interactions Phong model Shading polygons Shading in OpenGL
Overview Shading Shading Light-material interactions Phong model Shading polygons Shading in OpenGL Why we need shading Suppose we build a model of a sphere using many polygons and color it with glcolor.
More informationPerformance Plus Software Parameter Definitions
Performace Plus+ Software Parameter Defiitios/ Performace Plus Software Parameter Defiitios Chapma Techical Note-TG-5 paramete.doc ev-0-03 Performace Plus+ Software Parameter Defiitios/2 Backgroud ad Defiitios
More information9 x and g(x) = 4. x. Find (x) 3.6. I. Combining Functions. A. From Equations. Example: Let f(x) = and its domain. Example: Let f(x) = and g(x) = x x 4
1 3.6 I. Combiig Fuctios A. From Equatios Example: Let f(x) = 9 x ad g(x) = 4 f x. Fid (x) g ad its domai. 4 Example: Let f(x) = ad g(x) = x x 4. Fid (f-g)(x) B. From Graphs: Graphical Additio. Example:
More informationLecture Notes 6 Introduction to algorithm analysis CSS 501 Data Structures and Object-Oriented Programming
Lecture Notes 6 Itroductio to algorithm aalysis CSS 501 Data Structures ad Object-Orieted Programmig Readig for this lecture: Carrao, Chapter 10 To be covered i this lecture: Itroductio to algorithm aalysis
More informationBasic Optics: Index of Refraction
Basic Optics: Idex of Refractio Deser materials have lower speeds of light Idex of Refractio = where c = speed of light i vacuum v = velocity i medium Eve small chages ca create differece i Higher idex
More informationIMP: Superposer Integrated Morphometrics Package Superposition Tool
IMP: Superposer Itegrated Morphometrics Package Superpositio Tool Programmig by: David Lieber ( 03) Caisius College 200 Mai St. Buffalo, NY 4208 Cocept by: H. David Sheets, Dept. of Physics, Caisius College
More informationGraphics (Output) Primitives. Chapters 3 & 4
Graphics (Output) Primitives Chapters 3 & 4 Graphic Output ad Iput Pipelie Sca coversio coverts primitives such as lies, circles, etc. ito pixel values geometric descriptio Þ a fiite scee area Clippig
More informationThree-Dimensional Graphics V. Guoying Zhao 1 / 55
Computer Graphics Three-Dimensional Graphics V Guoying Zhao 1 / 55 Shading Guoying Zhao 2 / 55 Objectives Learn to shade objects so their images appear three-dimensional Introduce the types of light-material
More informationcondition w i B i S maximum u i
ecture 10 Dyamic Programmig 10.1 Kapsack Problem November 1, 2004 ecturer: Kamal Jai Notes: Tobias Holgers We are give a set of items U = {a 1, a 2,..., a }. Each item has a weight w i Z + ad a utility
More informationSecond-Order Domain Decomposition Method for Three-Dimensional Hyperbolic Problems
Iteratioal Mathematical Forum, Vol. 8, 013, o. 7, 311-317 Secod-Order Domai Decompositio Method for Three-Dimesioal Hyperbolic Problems Youbae Ju Departmet of Applied Mathematics Kumoh Natioal Istitute
More informationLecturers: Sanjam Garg and Prasad Raghavendra Feb 21, Midterm 1 Solutions
U.C. Berkeley CS170 : Algorithms Midterm 1 Solutios Lecturers: Sajam Garg ad Prasad Raghavedra Feb 1, 017 Midterm 1 Solutios 1. (4 poits) For the directed graph below, fid all the strogly coected compoets
More informationUH-MEM: Utility-Based Hybrid Memory Management. Yang Li, Saugata Ghose, Jongmoo Choi, Jin Sun, Hui Wang, Onur Mutlu
UH-MEM: Utility-Based Hybrid Memory Maagemet Yag Li, Saugata Ghose, Jogmoo Choi, Ji Su, Hui Wag, Our Mutlu 1 Executive Summary DRAM faces sigificat techology scalig difficulties Emergig memory techologies
More informationCounting Regions in the Plane and More 1
Coutig Regios i the Plae ad More 1 by Zvezdelia Stakova Berkeley Math Circle Itermediate I Group September 016 1. Overarchig Problem Problem 1 Regios i a Circle. The vertices of a polygos are arraged o
More informationMorgan Kaufmann Publishers 26 February, COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. Chapter 5
Morga Kaufma Publishers 26 February, 28 COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter 5 Set-Associative Cache Architecture Performace Summary Whe CPU performace icreases:
More informationXIV. Congress of the International Society for Photogrammetry Hamburg 1980
XIV. Cogress of the Iteratioal Society for Photogrammetry Hamburg 980 Commissio V Preseted Paper ALTAN, M. O. Techical Uiversity of Istabul Chair of Photograrretry ad Adjustmet A COMPARISON BETWEEN -PARAMETER
More information( n+1 2 ) , position=(7+1)/2 =4,(median is observation #4) Median=10lb
Chapter 3 Descriptive Measures Measures of Ceter (Cetral Tedecy) These measures will tell us where is the ceter of our data or where most typical value of a data set lies Mode the value that occurs most
More informationEvaluation scheme for Tracking in AMI
A M I C o m m u i c a t i o A U G M E N T E D M U L T I - P A R T Y I N T E R A C T I O N http://www.amiproject.org/ Evaluatio scheme for Trackig i AMI S. Schreiber a D. Gatica-Perez b AMI WP4 Trackig:
More informationVISUAL HULL CONSTRUCTION FROM SEMITRANSPARENT COLOURED SILHOUETTES
Iteratioal Joural of Computer Graphics & Aimatio (IJCGA) Vol.3, No.4, October 2013 VISUA HU CONSTRUCTION FROM SEMITRANSPARENT COOURED SIHOUETTES J R Raki ad M Boyapati a Trobe Uiversity, Australia ABSTRACT
More informationIntroduction to Sigma Notation
Itroductio to Siga Notatio Steph de Silva //207 What is siga otatio? is the capital Greek letter for the soud s I this case, it s just shorthad for su Siga otatio is what we use whe we have a series of
More informationA Practical and Robust Bump-mapping Technique for Today s GPUs
A Practical ad Robust Bump-mappig Techique for Today s GPUs Mark J. Kilgard NVIDIA Corporatio 3535 Moroe Street Sata Clara, CA 95051 (408) 615-2500 mjk@vidia.com March 30, 2000 Copyright NVIDIA Corporatio,
More informationn n B. How many subsets of C are there of cardinality n. We are selecting elements for such a
4. [10] Usig a combiatorial argumet, prove that for 1: = 0 = Let A ad B be disjoit sets of cardiality each ad C = A B. How may subsets of C are there of cardiality. We are selectig elemets for such a subset
More informationExact Minimum Lower Bound Algorithm for Traveling Salesman Problem
Exact Miimum Lower Boud Algorithm for Travelig Salesma Problem Mohamed Eleiche GeoTiba Systems mohamed.eleiche@gmail.com Abstract The miimum-travel-cost algorithm is a dyamic programmig algorithm to compute
More information. Written in factored form it is easy to see that the roots are 2, 2, i,
CMPS A Itroductio to Programmig Programmig Assigmet 4 I this assigmet you will write a java program that determies the real roots of a polyomial that lie withi a specified rage. Recall that the roots (or
More informationComputer Architecture ELEC3441
CPU-Memory Bottleeck Computer Architecture ELEC44 CPU Memory Lecture 8 Cache Dr. Hayde Kwok-Hay So Departmet of Electrical ad Electroic Egieerig Performace of high-speed computers is usually limited by
More informationNew Results on Energy of Graphs of Small Order
Global Joural of Pure ad Applied Mathematics. ISSN 0973-1768 Volume 13, Number 7 (2017), pp. 2837-2848 Research Idia Publicatios http://www.ripublicatio.com New Results o Eergy of Graphs of Small Order
More informationAccuracy Improvement in Camera Calibration
Accuracy Improvemet i Camera Calibratio FaJie L Qi Zag ad Reihard Klette CITR, Computer Sciece Departmet The Uiversity of Aucklad Tamaki Campus, Aucklad, New Zealad fli006, qza001@ec.aucklad.ac.z r.klette@aucklad.ac.z
More informationIllumination Distribution from Shadows
Illumiatio Distributio from Shadows Imari Sat0 Yoichi Sat0 Katsushi Ikeuchi Istitute of Idustrial Sciece, The Uiversity of Tokyo 7-22- 1 Roppogi, Miato-ku, Tokyo 106-8558, Japa { imarik, ysato, ki} 0iis.u-tokyo.ac.jp
More informationA New Morphological 3D Shape Decomposition: Grayscale Interframe Interpolation Method
A ew Morphological 3D Shape Decompositio: Grayscale Iterframe Iterpolatio Method D.. Vizireau Politehica Uiversity Bucharest, Romaia ae@comm.pub.ro R. M. Udrea Politehica Uiversity Bucharest, Romaia mihea@comm.pub.ro
More informationNON-LINEAR MODELLING OF A GEOTHERMAL STEAM PIPE
14thNew Zealad Workshop 1992 NON-LNEAR MODELLNG OF A GEOTHERMAL STEAM PPE Y. Huag ad D. H. Freesto Geothermal stitute, Uiversity of Aucklad SUMMARY Recet work o developig a o-liear model for a geothermal
More informationSD vs. SD + One of the most important uses of sample statistics is to estimate the corresponding population parameters.
SD vs. SD + Oe of the most importat uses of sample statistics is to estimate the correspodig populatio parameters. The mea of a represetative sample is a good estimate of the mea of the populatio that
More informationCS5620 Intro to Computer Graphics
So Far wireframe hidden surfaces Next step 1 2 Light! Need to understand: How lighting works Types of lights Types of surfaces How shading works Shading algorithms What s Missing? Lighting vs. Shading
More informationEE123 Digital Signal Processing
Last Time EE Digital Sigal Processig Lecture 7 Block Covolutio, Overlap ad Add, FFT Discrete Fourier Trasform Properties of the Liear covolutio through circular Today Liear covolutio with Overlap ad add
More informationBezier curves. Figure 2 shows cubic Bezier curves for various control points. In a Bezier curve, only
Edited: Yeh-Liag Hsu (998--; recommeded: Yeh-Liag Hsu (--9; last updated: Yeh-Liag Hsu (9--7. Note: This is the course material for ME55 Geometric modelig ad computer graphics, Yua Ze Uiversity. art of
More informationMarkov Chain Model of HomePlug CSMA MAC for Determining Optimal Fixed Contention Window Size
Markov Chai Model of HomePlug CSMA MAC for Determiig Optimal Fixed Cotetio Widow Size Eva Krimiger * ad Haiph Latchma Dept. of Electrical ad Computer Egieerig, Uiversity of Florida, Gaiesville, FL, USA
More informationThe number n of subintervals times the length h of subintervals gives length of interval (b-a).
Simulator with MadMath Kit: Riema Sums (Teacher s pages) I your kit: 1. GeoGebra file: Ready-to-use projector sized simulator: RiemaSumMM.ggb 2. RiemaSumMM.pdf (this file) ad RiemaSumMMEd.pdf (educator's
More informationFactor. 8th Grade Math. 2D Geometry: Transformations. 3 Examples/ Counterexamples. Vocab Word. Slide 3 / 227. Slide 4 / 227.
Slide / Slide / th Grade Math Geoetry: Trasforatios 0-0- www.jctl.org Slide / Slide / Table of otets Lis to PR saple questios No-alculator # No- alculator # lic o a topic to go to that sectio Trasforatios
More informationDerivation of perspective stereo projection matrices with depth, shape and magnification consideration
Derivatio of perspective stereo projectio matrices with depth, shape ad magificatio cosideratio Patrick Oberthür Jauary 2014 This essay will show how to costruct a pair of stereoscopic perspective projectio
More informationPolynomial Functions and Models. Learning Objectives. Polynomials. P (x) = a n x n + a n 1 x n a 1 x + a 0, a n 0
Polyomial Fuctios ad Models 1 Learig Objectives 1. Idetify polyomial fuctios ad their degree 2. Graph polyomial fuctios usig trasformatios 3. Idetify the real zeros of a polyomial fuctio ad their multiplicity
More informationAnalysis Metrics. Intro to Algorithm Analysis. Slides. 12. Alg Analysis. 12. Alg Analysis
Itro to Algorithm Aalysis Aalysis Metrics Slides. Table of Cotets. Aalysis Metrics 3. Exact Aalysis Rules 4. Simple Summatio 5. Summatio Formulas 6. Order of Magitude 7. Big-O otatio 8. Big-O Theorems
More information