Capturing light. Source: A. Efros
|
|
- Liliana Bailey
- 5 years ago
- Views:
Transcription
1 Capturg lght Source: A. Efros
2 Radometr What determes the brghtess of a mage pel? Sesor characterstcs Lght source propertes Eposure Surface shape ad oretato Optcs Surface reflectace propertes Slde b L. Fe-Fe
3 Radometr Radace: eerg carred b a ra Power per ut area perpedcular to the drecto of travel per ut sold agle Uts: Watts per square meter per sterada W m - sr - dω da
4 Sold Agle B aalog wth agle radas the sold agle subteded b a rego at a pot s the area projected o a ut sphere cetered at that pot The sold agle dω subteded b a patch of area da s gve b: dacos dω r dω θ A
5 Radometr Radace L: eerg carred b a ra Power per ut area perpedcular to the drecto of travel per ut sold agle Uts: Watts per square meter per sterada W m - sr - Irradace E: eerg arrvg at a surface E Icdet power per ut area ot foreshorteed Uts: W m - For a surface recevg radace L comg from dω the correspodg rradace s P da L L cosθ dω da cos da θ dωω da θ dacosθ dω
6 Radometr of th leses L: Radace emtted from P toward P E: Irradace fallg o P from the les What s the relatoshp betwee E ad L? Forsth & Poce Sec. 4..3
7 Radometr of th leses da The power δp receved b the les from P s o da δp The radace emtted from the les towards da s The rradace receved at P s z OP cosα z' OP ' cosα Area of the les: π d 4 π d L cosα δω 4 δp π d 4 π d cosα π d 4 E L cos α L z α 4 '/ cosα 4 z' cos Sold agle subteded b the les at P cosαα δω L
8 Radometr of th leses E π d 4 cos α 4 z' L Image rradace s learl related to scee radace Irradace s proportoal to the area of the les ad versel proportoal to the squared dstace betwee the les ad the mage plae The rradace falls off as the agle betwee the vewg ra ad the optcal as creases Forsth & Poce Sec. 4..3
9 Radometr of th leses E π d 4 cos α 4 z ' L Applcato: S B Kag ad R Wess Ca we calbrate a camera usg a S. B. Kag ad R. Wess Ca we calbrate a camera usg a mage of a flat tetureless Lamberta surface? ECCV 000.
10 From lght ras to pel values X E Δt E d π cos 4 α 4 z' L Z f E Δt Camera respose fucto: the mappg f from rradace to pel values Useful f we wat to estmate materal propertes Eables us to create hgh damc rage mages Source: S. Setz P. Debevec
11 From lght ras to pel values X E Δt E d π cos 4 α 4 z' L Z f E Δt Camera respose fucto: the mappg f from rradace to pel values For more fo P. E. Debevec ad J. Malk. Recoverg Hgh Damc Rage Radace Maps from Photographs. I SIGGRAPH 97 August 997 Source: S. Setz P. Debevec
12 The teracto of lght ad surfaces What happes whe a lght ra hts a pot o a object? Some of the lght gets absorbed coverted to other forms of eerg e.g. heat Some gets trasmtted through the object possbl bet through refracto Or scattered sde the object subsurface scatterg Some gets reflected possbl multple drectos at oce Reall complcated thgs ca happe fluorescece Let s cosder the case of reflecto detal Lght comg from a sgle drecto could be reflected all drectos. How ca we descrbe the amout of lght reflected each drecto? Slde b Steve Setz
13 Bdrectoal reflectace dstrbuto fucto BRDF Model of local reflecto that tells how brght a surface appears whe vewed from oe drecto whe lght falls o t from aother whe lght falls o t from aother Defto: rato of the radace the outgog drecto to rradace the cdet drecto φ θ φ θ φ θ φ θ L L e e e e e e surface ormal ω θ φ θ φ φ θ φ φ θ φ θ ρ d L E e e e e e e e e cos Radace leavg a surface a partcular drecto: add cotrbutos from ever comg drecto Ω e e d L ω θ φ θ φ θ φ θ ρ cos
14 BRDF s ca be credbl complcated
15 Dffuse reflecto Lght s reflected equall all drectos Dull matte surfaces lke chalk or late pat Mcrofacets scatter comg lght radoml BRDF s costat Albedo: fracto of cdet rradace reflected b the surface Radost: total power leavg the surface per ut area regardless of drecto
16 Dffuse reflecto: Lambert s law Vewed brghtess does ot deped o vewg drecto but t does deped o drecto of llumato B S ρ d d S B: radost ρ: albedo : ut ormal S: source vector magtude proportoal to test of the source
17 Specular reflecto Radato arrvg alog a source drecto leaves alog the specular drecto source drecto reflected about ormal Some fracto s absorbed some reflected O real surfaces eerg usuall goes to a lobe of drectos Phog model: reflected eerg falls of wth cos δθ Lamberta + specular model: sum of dffuse ad specular term
18 Specular reflecto Movg the lght source Chagg the epoet
19 Photometrc stereo shape from shadg Ca we recostruct the shape of a object based o shadg cues?
20 Photometrc stereo Assume: A Lamberta object A local shadg model each pot o a surface receves lght ol from sources vsble at that pot A set of kow lght source drectos A set of pctures of a object obtaed eactl the same camera/object cofgurato but usg dfferet sources Orthographc projecto Goal: recostruct object shape ad albedo S S S??? Forsth & Poce Sec. 5.4
21 Surface model: Moge patch Forsth & Poce Sec. 5.4
22 Image model Kow: source vectors S j ad pel values I j We also assume that the respose fucto of the camera s a lear scalg b a factor of k Combe the ukow ormal ad albedo ρ to oe vector g ad dthe scalg costat t k ad source vectors S j to aother vector V j: I j k B k ρ S j ρ k S j g V V j Forsth & Poce Sec. 5.4
23 Least squares problem For each pel we obta a lear sstem: I I I V M M V V T T T g 3 3 kow kow ukow Obta least-squares soluto for g Sce s the ut ormal ρ s gve b the magtude of g ad t should be less tha Fall g / ρ Forsth & Poce Sec. 5.4
24 Eample Recovered albedo Recovered ormal feld Forsth & Poce Sec. 5.4
25 Recoverg a surface from ormals Recall the surface s wrtte as If we wrte the estmated vector g as f g Ths meas the ormal has the form: f + f f f + g g g 3 The we obta values for the partal dervatves of the surface: f g g 3 f g g 3 Forsth & Poce Sec. 5.4
26 Recoverg a surface from ormals Itegrablt: for the surface f to est the med secod partal dervatves must be equal: g g 3 g g 3 practce the should at least be smlar We ca ow recover the surface heght at a pot b tegrato alog some path e.g. f 0 f s ds + 0 f tdt + c for robustess ca take tegrals over ma dfferet paths ad average the results Forsth & Poce Sec. 5.4
27 Surface recovered b tegrato Forsth & Poce Sec. 5.4
28 Lmtatos Orthographc camera model Smplstc reflectace ad lghtg model o shadows o terreflectos o mssg data Itegrato s trck
29 Fdg the drecto of the lght source I S + A Full 3D case: z z I I S S Full 3D case: S z z I A S M M M M M I S For pots o the occludg cotour: I I A S M M M M I A P. llus ad J.-O. Ekludh Automatc estmato of the projected lght source drecto CVPR 00
30 Fdg the drecto of the lght source P. llus ad J.-O. Ekludh Automatc estmato of the projected lght source drecto CVPR 00
31 Applcato: Detectg composte photos Real photo Fake photo
Light 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 informationCapturing light. Source: A. Efros
Capturing light Source: A. Efros Review Pinhole projection models What are vanishing points and vanishing lines? What is orthographic projection? How can we approximate orthographic projection? Lenses
More informationReflection models. Rendering equation. Taxonomy 2. Taxonomy 1. Digital Image Synthesis Yung-Yu Chuang 11/01/2005
Rederg equato Reflecto models Dgtal Image Sythess Yug-Yu Chuag 11/01/005 wth sldes by Pat Haraha ad Matt Pharr Taxoomy 1 ( xyt,,, θ, φλ, ) ( xyt,,, θφλ,, ) Geeral fucto = 1D Scatterg fucto = 9D out Assume
More informationEinführung in Visual Computing
Eführug Vsual Computg 868 Global Illumato Werer Purgathofer Surface-Rederg Methods polygo rederg methods ray tracg global llumato evromet mappg teture mappg bump mappg Werer Purgathofer Global Illumato
More information1-D matrix method. U 4 transmitted. incident U 2. reflected U 1 U 5 U 3 L 2 L 3 L 4. EE 439 matrix method 1
-D matrx method We ca expad the smple plae-wave scatterg for -D examples that we ve see to a more versatle matrx approach that ca be used to hadle may terestg -D problems. The basc dea s that we ca break
More informationFitting. We ve learned how to detect edges, corners, blobs. Now what? We would like to form a. compact representation of
Fttg Fttg We ve leared how to detect edges, corers, blobs. Now what? We would lke to form a hgher-level, h l more compact represetato of the features the mage b groupg multple features accordg to a smple
More informationProf. Feng Liu. Winter /24/2019
Prof. Feg Lu Wter 209 http://www.cs.pd.edu/~flu/courses/cs40/ 0/24/209 Last Tme Feature detecto 2 Toda Feature matchg Fttg The followg sldes are largel from Prof. S. Lazebk 3 Wh etract features? Motvato:
More informationBezier curves. 1. Defining a Bezier curve. A closed Bezier curve can simply be generated by closing its characteristic polygon
Curve represetato Copyrght@, YZU Optmal Desg Laboratory. All rghts reserved. Last updated: Yeh-Lag Hsu (--). Note: Ths s the course materal for ME55 Geometrc modelg ad computer graphcs, Yua Ze Uversty.
More informationEight Solved and Eight Open Problems in Elementary Geometry
Eght Solved ad Eght Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew eght prevous proposed ad solved problems of elemetary
More informationPHY 114 A General Physics II 11 AM-12:15 PM TR Olin 101
PHY 4 A Geeral Physcs II AM-:5 PM TR Ol Pla or Lecture 9 (Chapter 36): Optcal propertes o lght. Mrror relectos. Images lat ad sphercal mrrors 4/4/ PHY 4 A Sprg -- Lecture 9 4/4/ PHY 4 A Sprg -- Lecture
More informationPoint Estimation-III: General Methods for Obtaining Estimators
Pot Estmato-III: Geeral Methods for Obtag Estmators RECAP 0.-0.6 Data: Radom Sample from a Populato of terest o Real valued measuremets: o Assumpto (Hopefully Reasoable) o Model: Specfed Probablty Dstrbuto
More informationEight Solved and Eight Open Problems in Elementary Geometry
Eght Solved ad Eght Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew eght prevous proposed ad solved problems of elemetary
More informationNine Solved and Nine Open Problems in Elementary Geometry
Ne Solved ad Ne Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew e prevous proposed ad solved problems of elemetary D geometry
More informationComputer Graphics - Week 11
Computer Graphcs - Wee Begt-Olaf Scheder IBM T.J. Watso Research Ceter Questos about Last Wee? Computer Graphcs Wee Begt-Olaf Scheder, 999 Assgmet 4 You should have started by ow There wll ot be a exteso
More informationOffice Hours. COS 341 Discrete Math. Office Hours. Homework 8. Currently, my office hours are on Friday, from 2:30 to 3:30.
Oce Hours Curretly, my oce hours are o Frday, rom :30 to 3:30. COS 31 Dscrete Math 1 Oce Hours Curretly, my oce hours are o Frday, rom :30 to 3:30. Nobody seems to care. Chage oce hours? Tuesday, 8 PM
More information3D Polygon Rendering Pipeline
2008 סמסטר ב' ליאור שפירא קורס גרפיקה ממוחשבת 3D Rederg Ppele (for drect llumato) 3D Polygo Rederg Ppele Sca Coverso & Shadg Thomas Fukhouser Prceto Uversty C0S 426, Fall 1999 3D Prmtves 3D Modelg Coordates
More informationThe propagation of light pollution in the atmosphere
Mo. Not. R. Astro. Soc. xxx, xx-xx () The propagato of lght polluto the atmosphere P. Czao * ad F. Falch, Isttuto d Sceza e Tecologa dell Iquameto Lumoso (ISTIL), Va Roma 3, I-366 Thee, Italy CeloBuo,
More informationECE Digital Image Processing and Introduction to Computer Vision
ECE59064 Dgtal Image Processg ad Itroducto to Computer Vso Depart. of ECE NC State Uverst Istructor: Tafu Matt Wu Sprg 07 Outle Recap Le Segmet Detecto Fttg Least square Total square Robust estmator Hough
More informationFace Recognition using Supervised & Unsupervised Techniques
Natoal Uversty of Sgapore EE5907-Patter recogto-2 NAIONAL UNIVERSIY OF SINGAPORE EE5907 Patter Recogto Project Part-2 Face Recogto usg Supervsed & Usupervsed echques SUBMIED BY: SUDEN NAME: harapa Reddy
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 informationCS 2710 Foundations of AI Lecture 22. Machine learning. Machine Learning
CS 7 Foudatos of AI Lecture Mache learg Mlos Hauskrecht mlos@cs.ptt.edu 539 Seott Square Mache Learg The feld of mache learg studes the desg of computer programs (agets) capable of learg from past eperece
More informationChEn 475 Statistical Analysis of Regression Lesson 1. The Need for Statistical Analysis of Regression
Statstcal-Regresso_hadout.xmcd Statstcal Aalss of Regresso ChE 475 Statstcal Aalss of Regresso Lesso. The Need for Statstcal Aalss of Regresso What do ou do wth dvdual expermetal data pots? How are the
More informationRadiometry. Radiometry. Measuring Angle. Solid Angle. Radiance
Radiometry Radiometry Computer Vision I CSE5A ecture 5-Part II Read Chapter 4 of Ponce & Forsyth Solid Angle Irradiance Radiance BRDF ambertian/phong BRDF Measuring Angle Solid Angle By analogy with angle
More informationDescriptive Statistics: Measures of Center
Secto 2.3 Descrptve Statstcs: Measures of Ceter Frequec dstrbutos are helpful provdg formato about categorcal data, but wth umercal data we ma wat more formato. Statstc: s a umercal measure calculated
More informationA Robust Model-Based Approach for 3D Head Tracking in Video Sequences
A Robust Model-Based Approach for 3D Head Trackg Vdeo Sequeces Marus Malcu ad Fraçose Prêteux Isttut Natoal des Télécommucatos ARTEMIS Project Ut {Marus.Malcu, Fracose.Preteux}@t-evry.fr Abstract We preset
More information3D Face Recognition without Facial Surface Reconstruction
Techo - Computer Scece Departmet - Techcal Report CIS-003-05 - 003 Abstract Recetly, a 3D face recogto approach based o geometrc varat sgatures, has bee proposed. The key dea of the algorthm s a represetato
More informationFor all questions, answer choice E) NOTA" means none of the above answers is correct. A) 50,500 B) 500,000 C) 500,500 D) 1,001,000 E) NOTA
For all questos, aswer choce " meas oe of the above aswers s correct.. What s the sum of the frst 000 postve tegers? A) 50,500 B) 500,000 C) 500,500 D),00,000. What s the sum of the tegers betwee 00 ad
More informationReflectance & Lighting
Reflectance & Lighting Computer Vision I CSE5A Lecture 6 Last lecture in a nutshell Need for lenses (blur from pinhole) Thin lens equation Distortion and aberrations Vignetting CS5A, Winter 007 Computer
More informationMachine Learning: Algorithms and Applications
/03/ Mache Learg: Algorthms ad Applcatos Florao Z Free Uversty of Boze-Bolzao Faculty of Computer Scece Academc Year 0-0 Lecture 3: th March 0 Naïve Bayes classfer ( Problem defto A trag set X, where each
More informationAutomated approach for the surface profile measurement of moving objects based on PSP
Uversty of Wollogog Research Ole Faculty of Egeerg ad Iformato Sceces - Papers: Part B Faculty of Egeerg ad Iformato Sceces 207 Automated approach for the surface profle measuremet of movg objects based
More informationLP: example of formulations
LP: eample of formulatos Three classcal decso problems OR: Trasportato problem Product-m problem Producto plag problem Operatos Research Massmo Paolucc DIBRIS Uversty of Geova Trasportato problem The decso
More informationRadiometry. Reflectance & Lighting. Solid Angle. Radiance. Radiance Power is energy per unit time
Radiometry Reflectance & Lighting Computer Vision I CSE5A Lecture 6 Read Chapter 4 of Ponce & Forsyth Homework 1 Assigned Outline Solid Angle Irradiance Radiance BRDF Lambertian/Phong BRDF By analogy with
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 informationSome Interesting SAR Change Detection Studies
Some Iterestg SAR Chage Detecto Studes Lesle M. ovak Scetfc Sstems Compa, Ic. 500 West Cummgs Park, Sute 3000 Wobur, MA 080 USA E-mal lovak@ssc.co ovakl@charter.et ABSTRACT Performace results of coheret
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 informationAnnouncements. Fitting: Announcements. Some seam carving results 9/24/2009. Thursday, Sept 24 Kristen Grauman UT-Austin
9/4/9 Aoucemets Fttg: Deformable cotours Thursday, Sept 4 Krste Grauma UT-Aust Next week : guest lectures Tuesday : Backgroud modelg Thursday : Image formato Yog Jae ad I are ot avalable for offce hours
More informationEffects of Exterior Orientation Elements on Direct Georeferencing in POS-Supported Aerial Photogrammetry
Proceedgs of the 8th Iteratoal mposum o patal Accurac Assessmet atural Resources ad Evrometal ceces hagha P. R. Cha Jue 5-7 008 pp. 30-36 Effects of Eteror Oretato Elemets o Drect Georeferecg PO-upported
More informationLocal vs. Global Illumination & Radiosity
Local vs. Global Illumato & Radosty Last Tme? Ray Castg & Ray-Object Itesecto Recusve Ray Tacg Dstbuted Ray Tacg A ealy applcato of adatve heat tasfe stables. Local Illumato BRDF Ideal Dffuse Reflectace
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 informationReliable Surface Extraction from Point-Clouds using Scanner-Dependent Parameters
1 Relable Surface Extracto from Pot-Clouds usg Scaer-Depedet Parameters Hrosh Masuda 1, Ichro Taaka 2, ad Masakazu Eomoto 3 1 The Uversty of Tokyo, masuda@sys.t.u-tokyo.ac.jp 2 Tokyo Dek Uversty, taaka@cck.deda.ac.jp
More informationPhotometric Stereo. Lighting and Photometric Stereo. Computer Vision I. Last lecture in a nutshell BRDF. CSE252A Lecture 7
Lighting and Photometric Stereo Photometric Stereo HW will be on web later today CSE5A Lecture 7 Radiometry of thin lenses δa Last lecture in a nutshell δa δa'cosα δacos β δω = = ( z' / cosα ) ( z / cosα
More informationChapter 3 Descriptive Statistics Numerical Summaries
Secto 3.1 Chapter 3 Descrptve Statstcs umercal Summares Measures of Cetral Tedecy 1. Mea (Also called the Arthmetc Mea) The mea of a data set s the sum of the observatos dvded by the umber of observatos.
More informationA question from Piazza
Radiometry, Reflectance, Lights CSE 252A Lecture 6 A question from Piazza 1 Announcements HW1 posted HWO graded, will be returned today If anyone has any registration issues, talk to me. Appearance: lighting,
More informationDEEP (Displacement Estimation Error Back-Propagation) Method for Cascaded ViSPs (Visually Servoed Paired Structured Light Systems)
DEEP (Dsplacemet Estmato Error Back-Propagato) Method for Cascaded VSPs (Vsually Servoed Pared Structured Lght Systems) Haem Jeo 1), Jae-Uk Sh 2), Wachoel Myeog 3), Yougja Km 4), ad *Hyu Myug 5) 1), 3),
More informationMonte Carlo 1: Integration
Monte Carlo : Integraton Prevous lecture: Analytcal llumnaton formula Ths lecture: Monte Carlo Integraton Revew random varables and probablty Samplng from dstrbutons Samplng from shapes Numercal calculaton
More informationEE Light & Image Formation
EE 576 - Light & Electric Electronic Engineering Bogazici University January 29, 2018 EE 576 - Light & EE 576 - Light & The image of a three-dimensional object depends on: 1. Shape 2. Reflectance properties
More informationComputer Graphics. Jeng-Sheng Yeh 葉正聖 Ming Chuan University (modified from Bing-Yu Chen s slides)
Computer Graphcs Jeng-Sheng Yeh 葉正聖 Mng Chuan Unversty (modfed from Bng-Yu Chen s sldes) llumnaton and Shadng llumnaton Models Shadng Models for Polygons Surface Detal Shadows Transparency Global llumnaton
More informationOn a Sufficient and Necessary Condition for Graph Coloring
Ope Joural of Dscrete Matheatcs, 04, 4, -5 Publshed Ole Jauary 04 (http://wwwscrporg/joural/ojd) http://dxdoorg/0436/ojd04400 O a Suffcet ad Necessary Codto for raph Colorg Maodog Ye Departet of Matheatcs,
More informationVanishing Point Detection: Representation Analysis and New Approaches
Publshed the Proceedgs of the th Iteratoal Coferece o Image Aalyss ad Processg (ICIAP ). IEEE. Persoal use of ths materal s permtted. However, permsso to reprt/republsh ths materal for advertsg or promotoal
More informationBlind Steganalysis for Digital Images using Support Vector Machine Method
06 Iteratoal Symposum o Electrocs ad Smart Devces (ISESD) November 9-30, 06 Bld Stegaalyss for Dgtal Images usg Support Vector Mache Method Marcelus Hery Meor School of Electrcal Egeerg ad Iformatcs Badug
More informationBeijing University of Technology, Beijing , China; Beijing University of Technology, Beijing , China;
d Iteratoal Coferece o Machery, Materals Egeerg, Chemcal Egeerg ad Botechology (MMECEB 5) Research of error detecto ad compesato of CNC mache tools based o laser terferometer Yuemg Zhag, a, Xuxu Chu, b
More informationMOTION RECOVERY BASED ON FEATURE EXTRACTION FROM 2D IMAGES
MOTION RECOVERY BASED ON FEATURE EXTRACTION FROM 2D IMAGES Jahu Zhao, Lg L 2 ad Kwoh Chee Keog 3,3 School of Computer Egeerg, Nayag Techologcal Uversty, Sgapore, 639798 2 School of Computg, Curt Uversty
More informationIntro to Scientific Computing: Solutions
Itro to Scietific Computig: Solutios Dr. David M. Goulet. How may steps does it take to separate 3 objects ito groups of 4? We start with 5 objects ad apply 3 steps of the algorithm to reduce the pile
More informationLights, Surfaces, and Cameras. Light sources emit photons Surfaces reflect & absorb photons Cameras measure photons
Reflectance 1 Lights, Surfaces, and Cameras Light sources emit photons Surfaces reflect & absorb photons Cameras measure photons 2 Light at Surfaces Many effects when light strikes a surface -- could be:
More informationEye Detection and Tracking in Image with Complex Background
Volume No.4, APRIL ISSN 79-847 Joural of Emergg reds Computg ad Iformato Sceces - CIS Joural. All rghts reserved. http://www.csjoural.org Ee Detecto ad rackg Image wth Comple Backgroud Mohammadal Azm Kasha,
More informationImage Analysis. Segmentation by Fitting a Model. Christophoros Nikou We ve learned how to detect edges, corners, blobs. Now what?
Image Aalyss Fttg Segmetato y Fttg a Model Chrstophoros Nkou ckou@cs.uo.gr Images take from: D. Forsyth ad J. Poce. Computer Vso: A Moder Approach, Pretce Hall, 003. Computer Vso course y Svetlaa Lazek,
More informationA Comparison of Univariate Smoothing Models: Application to Heart Rate Data Marcus Beal, Member, IEEE
A Comparso of Uvarate Smoothg Models: Applcato to Heart Rate Data Marcus Beal, Member, IEEE E-mal: bealm@pdx.edu Abstract There are a umber of uvarate smoothg models that ca be appled to a varety of olear
More informationA MapReduce-Based Multiple Flow Direction Runoff Simulation
A MapReduce-Based Multple Flow Drecto Ruoff Smulato Ahmed Sdahmed ad Gyozo Gdofalv GeoIformatcs, Urba lag ad Evromet, KTH Drottg Krstas väg 30 100 44 Stockholm Telephoe: +46-8-790 8709 Emal:{sdahmed, gyozo}@
More informationMINIMIZATION OF THE VALUE OF DAVIES-BOULDIN INDEX
MIIMIZATIO OF THE VALUE OF DAVIES-BOULDI IDEX ISMO ÄRÄIE ad PASI FRÄTI Departmet of Computer Scece, Uversty of Joesuu Box, FI-800 Joesuu, FILAD ABSTRACT We study the clusterg problem whe usg Daves-Bould
More informationMonte Carlo 1: Integration
Monte Carlo : Integraton Prevous lecture: Analytcal llumnaton formula Ths lecture: Monte Carlo Integraton Revew random varables and probablty Samplng from dstrbutons Samplng from shapes Numercal calculaton
More informationClustering documents with vector space model using n-grams
Clusterg documets wth vector space model usg -grams Klas Skogmar, d97ksk@efd.lth.se Joha Olsso, d97jo@efd.lth.se Lud Isttute of Techology Supervsed by: Perre Nugues, Perre.Nugues@cs.lth.se Abstract Ths
More informationCENG 477 Introduction to Computer Graphics. Ray Tracing: Shading
CENG 477 Introduction to Computer Graphics Ray Tracing: Shading Last Week Until now we learned: How to create the primary rays from the given camera and image plane parameters How to intersect these rays
More informationITEM ToolKit Technical Support Notes
ITEM ToolKt Notes Fault Tree Mathematcs Revew, Ic. 2875 Mchelle Drve Sute 300 Irve, CA 92606 Phoe: +1.240.297.4442 Fax: +1.240.297.4429 http://www.itemsoft.com Page 1 of 15 6/1/2016 Copyrght, Ic., All
More informationInternational Mathematical Forum, 1, 2006, no. 31, ON JONES POLYNOMIALS OF GRAPHS OF TORUS KNOTS K (2, q ) Tamer UGUR, Abdullah KOPUZLU
Iteratoal Mathematcal Forum,, 6, o., 57-54 ON JONES POLYNOMIALS OF RAPHS OF TORUS KNOTS K (, q ) Tamer UUR, Abdullah KOPUZLU Atatürk Uverst Scece Facult Dept. of. Math. 54 Erzurum, Turkey tugur@atau.edu.tr
More informationDesign and Correction of Optical Systems
Desg ad Correcto of Optcal Sstems Lecture : Bascs 07-04-07 Herbert Gross Summer term 07 www.ap.u-ea.de Prelmar Schedule - DCS 07 07.04. Bascs 4.04. Materals ad Compoets 3.04. Paraxal Optcs 4 8.04. Optcal
More informationPaths, diffuse interreflections, caching and radiometry. D.A. Forsyth
Paths, diffuse interreflections, caching and radiometry D.A. Forsyth How we got here We want to render diffuse interreflections strategy: compute approximation B-hat, then gather B = E +(ρk)e +(ρk)( ˆB
More informationThe Light Field. Last lecture: Radiometry and photometry
The Light Field Last lecture: Radiometry and photometry This lecture: Light field = radiance function on rays Conservation of radiance Measurement equation Throughput and counting rays Irradiance calculations
More informationEstimating Feasibility Using Multiple Surrogates and ROC Curves
Estmatg Feasblty Usg Multple Surrogates ad ROC Curves Arba Chaudhur * Uversty of Florda, Gaesvlle, Florda, 3601 Rodolphe Le Rche École Natoale Supéreure des Mes de Sat-Étee, Sat-Étee, Frace ad CNRS LIMOS
More informationNormals. In OpenGL the normal vector is part of the state Set by glnormal*()
Ray Tracig 1 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
More informationCLUSTERING ASSISTED FUNDAMENTAL MATRIX ESTIMATION
CLUSERING ASSISED FUNDAMENAL MARIX ESIMAION Hao Wu ad Y Wa School of Iformato Scece ad Egeerg, Lazhou Uversty, Cha wuhao1195@163com, wayjs@163com ABSRAC I computer vso, the estmato of the fudametal matrx
More informationUnsupervised visual learning of three-dimensional objects using a modular network architecture
PERGAMON Neural Networks 12 (1999) 1037 1051 Neural Networks www.elsever.com/locate/euet Usupervsed vsual learg of three-dmesoal objects usg a modular etwork archtecture H. Ado a, *, S. Suzuk a,b, T. Fujta
More informationDesign and Correction of Optical Systems
Desg ad Correcto of Optcal Sstems Lecture : Bascs 04-04-09 Herbert Gross Wter term 04 www.ap.u-ea.de Overvew Tme: Wedesda, 8.5 9.45 Locato: HS 3, Haus 3 Web page o IAP homepage uder learg/materals provdes
More informationFace Authentication for Multiple Subjects Using Eigenflow
Face Authetcato for Multple Subjects Usg Egeflow Xaomg Lu Tsuha Che ad B.V.K. Vjaya Kumar Advaced Multmeda Processg Lab Techcal Report AMP -5 Aprl 2 Electrcal ad Computer Egeerg Carege Mello Uversty Pttsburgh,
More informationCSE 681 Illumination and Phong Shading
CSE 681 Illumination and Phong Shading Physics tells us What is Light? We don t see objects, we see light reflected off of objects Light is a particle and a wave The frequency of light What is Color? Our
More informationAPR 1965 Aggregation Methodology
Sa Joaqu Valley Ar Polluto Cotrol Dstrct APR 1965 Aggregato Methodology Approved By: Sged Date: March 3, 2016 Araud Marjollet, Drector of Permt Servces Backgroud Health rsk modelg ad the collecto of emssos
More informationAn Optimal Thresholding Method for the Voxel Coloring in the 3D Shape Reconstruction
ICCAS00 Jue -, KINTEX, Gyeogg-Do, Korea A Optmal Thresholdg Method or the oxel Colorg the D Shape Recostructo Soo-Youg Ye*, Hyo-Sug Km*, Youg-Youl Y*, ad K-Go Nam ** * Dept. o Electrocs Egr., Pusa Natoal
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 informationAPPLICATION OF CLUSTERING METHODS IN BANK S PROPENSITY MODEL
APPLICATION OF CLUSTERING METHODS IN BANK S PROPENSITY MODEL Sergej Srota Haa Řezaková Abstract Bak s propesty models are beg developed for busess support. They should help to choose clets wth a hgher
More informationIntroduction to Radiosity
Introduction to Radiosity Produce photorealistic pictures using global illumination Mathematical basis from the theory of heat transfer Enables color bleeding Provides view independent representation Unfortunately,
More informationAnnouncement. Lighting and Photometric Stereo. Computer Vision I. Surface Reflectance Models. Lambertian (Diffuse) Surface.
Lighting and Photometric Stereo CSE252A Lecture 7 Announcement Read Chapter 2 of Forsyth & Ponce Might find section 12.1.3 of Forsyth & Ponce useful. HW Problem Emitted radiance in direction f r for incident
More informationdq dt I = Irradiance or Light Intensity is Flux Φ per area A (W/m 2 ) Φ =
Radiometry (From Intro to Optics, Pedrotti -4) Radiometry is measurement of Emag radiation (light) Consider a small spherical source Total energy radiating from the body over some time is Q total Radiant
More informationApplication of Genetic Algorithm for Computing a Global 3D Scene Exploration
Joural of Software Egeerg ad Applcatos, 2011, 4, 253-258 do:10.4236/jsea.2011.44028 Publshed Ole Aprl 2011 (http://www.scrp.org/joural/jsea) 253 Applcato of Geetc Algorthm for Computg a Global 3D Scee
More informationDelay based Duplicate Transmission Avoid (DDA) Coordination Scheme for Opportunistic routing
Delay based Duplcate Trasmsso Avod (DDA) Coordato Scheme for Opportustc routg Ng L, Studet Member IEEE, Jose-Fera Martez-Ortega, Vcete Heradez Daz Abstract-Sce the packet s trasmtted to a set of relayg
More informationCOMSC 2613 Summer 2000
Programmg II Fal Exam COMSC 63 Summer Istructos: Name:. Prt your ame the space provded Studet Id:. Prt your studet detfer the space Secto: provded. Date: 3. Prt the secto umber of the secto whch you are
More informationTransistor/Gate Sizing Optimization
Trasstor/Gate Szg Optmzato Gve: Logc etwork wth or wthout cell lbrary Fd: Optmal sze for each trasstor/gate to mmze area or power, both uder delay costrat Statc szg: based o tmg aalyss ad cosder all paths
More informationAnd if that 120MP Camera was cool
Reflectance, Lights and on to photometric stereo CSE 252A Lecture 7 And if that 120MP Camera was cool Large Synoptic Survey Telescope 3.2Gigapixel camera 189 CCD s, each with 16 megapixels Pixels are 10µm
More information2 General Regression Neural Network (GRNN)
4 Geeral Regresso Neural Network (GRNN) GRNN, as proposed b oald F. Specht [Specht 9] falls to the categor of probablstc eural etworks as dscussed Chapter oe. Ths eural etwork lke other probablstc eural
More informationPriority-based Packet Scheduling in Internet Protocol Television
EMERGING 0 : The Thrd Iteratoal Coferece o Emergg Network Itellgece Prorty-based Packet Schedulg Iteret Protocol Televso Mehmet Dez Demrc Computer Scece Departmet Istabul Uversty İstabul, Turkey e-mal:demrcd@stabul.edu.tr
More informationMoving Foreground Detection Based On Spatio-temporal Saliency
IJCSI Iteratoal Joural of Computer Scece Issues Vol. 10 Issue 1 No 3 Jauary 013 ISSN (Prt): 1694-0784 ISSN (Ole): 1694-0814 www.ijcsi.org 79 Movg Foregroud Detecto Based O Spato-temporal Salecy Yag Xa
More informationOutline. Area objects and spatial autocorrelation. Types of area object
Area objects ad spatal autocorrelato Outle Itroducto Geometrc propertes of areas Spatal autocorrelato: jos cout approach Spatal autocorrelato: Mora s I Spatal autocorrelato: Geary s C Spatal autocorrelato:
More informationANALYSIS OF VARIANCE WITH PARETO DATA
Proceedgs of the th Aual Coferece of Asa Pacfc Decso Sceces Isttute Hog Kog, Jue -8, 006, pp. 599-609. ANALYSIS OF VARIANCE WITH PARETO DATA Lakhaa Watthaacheewakul Departmet of Mathematcs ad Statstcs,
More informationPerformance Impact of Load Balancers on Server Farms
erformace Impact of Load Balacers o Server Farms Ypg Dg BMC Software Server Farms have gaed popularty for provdg scalable ad relable computg / Web servces. A load balacer plays a key role ths archtecture,
More informationLaplacian Meshes Deformation Based on the Offset of Sketching
JOURNAL OF SOFTWARE, VOL. 7, NO. 9, SEPTEMBER 202 2083 Laplaca Meshes Deformato Based o the Offset of Sketchg Sha Chemg School of Software, Harb Uversty of Scece ad Techology, Harb, Cha Emal: shachm@63.com
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 informationINFOGR Computer Graphics. J. Bikker - April-July Lecture 10: Shading Models. Welcome!
INFOGR Computer Graphics J. Bikker - April-July 2016 - Lecture 10: Shading Models Welcome! Today s Agenda: Introduction Light Transport Materials Sensors Shading INFOGR Lecture 10 Shading Models 3 Introduction
More informationCOMPARISON OF PARAMETERIZATION METHODS USED FOR B-SPLINE CURVE INTERPOLATION
Europea Joural of Techc COMPARISON OF PARAMETERIZATION METHODS USED FOR B-SPLINE CURVE INTERPOLATION Sıtı ÖZTÜRK, Cegz BALTA, Melh KUNCAN 2* Kocael Üverstes, Mühedsl Faültes, Eletro ve Haberleşme Mühedslğ
More informationScientific Visualization on Sparse Grids
Scetfc Vsualzato o Sparse Grds Chrsta Tetzel Computer Graphcs Group Am Wechselgarte 9 91058 Erlage Germay tetzel@formatk.u-erlage.de Matthas Hopf Thomas Ertl Vsualzato ad Iteractve Systems Group Bretwesestr.
More informationSelf-intersection Avoidance for 3-D Triangular Mesh Model
Self-tersecto Avodace for 3-D Tragular Mesh Model Habtamu Masse Aycheh 1) ad M Ho Kyug ) 1) Departmet of Computer Egeerg, Ajou Uversty, Korea, ) Departmet of Dgtal Meda, Ajou Uversty, Korea, 1) hab01@ajou.ac.kr
More informationComplex Filtering and Integration via Sampling
Overvew Complex Flterng and Integraton va Samplng Sgnal processng Sample then flter (remove alases) then resample onunform samplng: jtterng and Posson dsk Statstcs Monte Carlo ntegraton and probablty theory
More informationRegion Matching by Optimal Fuzzy Dissimilarity
Rego Matchg by Optmal Fuzzy Dssmlarty Zhaggu Zeg, Ala Fu ad Hog Ya School of Electrcal ad formato Egeerg The Uversty of Sydey Phoe: +6--935-6659 Fax: +6--935-3847 Emal: zzeg@ee.usyd.edu.au Abstract: Ths
More information