4.1 3D GEOMETRIC TRANSFORMATIONS
|
|
- Dina Lamb
- 5 years ago
- Views:
Transcription
1 MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN 29- Dep. of Compuer Science And Applicaions, SJCET, Palai D GEOMETRIC TRANSFORMATIONS Mehods for geomeric ransformaions and objec modeling in hree dimensions are eended from wo-dimensional mehods b including consideraions for he coordinae. We now ranslae an objec b specifing a hree-dimensional ranslaion vecor, which deermines how much he objec is o be moved in each of he hree coordinae direcions. Similarl, we scale an objec wih hree coordinae scaling facors. The eension for hree-dimensional roaion is less sraighforward. When we discussed wo-dimensional roaions in he plane, we needed o consider onl roaions abou aes ha were perpendicular o he plane. In hree-dimensional space, we can now selec an spaial orienaion for he roaion ais. Mos graphics packages handle hreedimensional roaion as a composie of hree roaions, one for each of he hree Caresian aes. Alernaivel, a user can easil se up a general roaion mari, given he orienaion of he ais and he required roaion angle. As in he wo-dimensional case, we epress geomeric ransformaions in mari form. An sequence of ransformaions is hen represened as, a gle mari, formed b concaenaing he marices for he individual ransformaions in he sequence. Transformaion Mari 33 : Scaling, Reflecion, Shearing, Roaion 3 : Translaion : Uniform global Scaling 3 : Homogeneous represenaion 4.. TRANSLATION In a hree-dimensional homogeneous coordinae represenaion, a poin is ranslaed (Fig. 4.) from posiion P = (,, ) o posiion P = (,, ) wih he mari operaion S L I F C K H E B J G D A,,
2 MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN 29- (Fig: 4.) An objec is ranslaed in hree dimensions b ransforming each of he defining poins of he objec. For an objec represened as a se of polgon surfaces, we ranslae each vere of each surface and redraw he polgon faces in he new posiion. We obain he inverse of he ranslaion mari in he given equaion b negaing he ranslaion disances,, and. This produces a ranslaion in he opposie direcion, and he produc of a ranslaion mari and is inverse produces he ideni mari ROTATION To generae a roaion ransformaion for an objec, we mus designae an ais of roaion (abou which he objec is o be roaed) and he amoun of angular roaion. Unlike wo-dimensional applicaions, where all ransformaions are carried ou in he plane, a hree-dimensional roaion can be specified around an line in space. The easies roaion aes o handle are hose ha are parallel o he coordinae aes. Also, we can use combinaions of coordinae ais roaions (along wih appropriae ranslaions) o specif an general roaion. B convenion, posiive roaion angles produce counerclockwise roaions abou a coordinae ais, if we are looking along he posiive half of he ais oward he coordinae origin his agrees wih our earlier discussion of roaion in wo dimensions, where posiive roaions in he plane are counerclockwise abou aes parallel o he ais. Coordinae-Aes Roaions X-ais roaion Y-ais roaion Z-ais roaion Dep. of Compuer Science And Applicaions, SJCET, Palai 95
3 MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN 29- Dep. of Compuer Science And Applicaions, SJCET, Palai 96 X-Ais Roaion Z-Ais Roaion Y-Ais Roaion An inverse roaion mari is formed b replacing he roaion angle. Negaive values for roaion angles generae roaions in a clockwise direcion, so he ideni mari is produced when an roaion mari is muliplied b is inverse. Since onl he e funcion is affeced b he change in sign of he roaion angle, he inverse mari can also be obained b inerchanging rows and columns. Tha is, we can calculae he inverse of an roaion mari R b evaluaing is ranspose (R - = R T ). This mehod for obaining an inverse mari holds also for an composie roaion mari General Three-Dimensional Roaions A roaion mari for an ais ha does no coincide wih a coordinae ais can be se up as a composie ransformaion involving combinaions of ranslaions and he coordinae-aes roaions. We obain he required composie mari b firs seing up he ransformaion sequence ha moves he seleced roaion ais ono one of he coordinae aes. Then we se up he roaion mari abou ha coordinae ais for he specified roaion angle. The las sep is o obain he inverse ransformaion sequence ha reurns he roaion ais o is original posiion.
4 MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN 29- In he special case where an objec is o be roaed abou an ais ha is parallel o one of he coordinae aes, we can aain he desired roaion wih he following ransformaion sequence. ) Translae he objec so ha he roaion ais coincides wih he parallel coordinae ais. 2) Perform he specified roaion abou ha ais. 3) Translae he objec so ha he roaion ais is moved back o is original posiion. The seps in his sequence are illusraed in Fig An coordinae posiion P on he objec in his figure is ransformed wih he sequence shown as P = -.R (θ).t.p Where he composie mari for he ransformaion is R (θ) =T -. R (θ).t This is of he same as he wo-dimensional ransformaion sequence for roaion abou an arbirar pivo poin. (Fig : 4.2) Dep. of Compuer Science And Applicaions, SJCET, Palai 97
5 MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN 29- When an objec is o be roaed abou an ais ha is no parallel o one of he coordinae aes, we need o perform some addiional ransformaions. In his case, we also need roaions o align he ais wih a seleced coordinae ais and o bring he ais back o is original orienaion Given he specificaions for he roaion ais and he roaion angle, we can accomplish he required roaion in five seps ) Translae he objec so ha he roaion ais pass= hrough he coordinae origin. 2) Roae he objec so ha he ais of roaion coincides wih one of he coordinae aes. 3) Perform he specified roaion abou ha coordinae ais. 4) Appl inverse roaions o bring he roaion ais back o is original orienaion. 5) Appl he inverse ranslaion o bring he roaion ais back o is original posiion. Dep. of Compuer Science And Applicaions, SJCET, Palai 98
6 MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN 29- Dep. of Compuer Science And Applicaions, SJCET, Palai 99
7 MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN 29- Dep. of Compuer Science And Applicaions, SJCET, Palai
8 MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN SCALING The mari epression or he scaling ransformaion of a posiion P = (,, ) relaive o he coordinae origin can be wrien as Where scaling parameers s, s, and s are assigned an posiive values. Eplici epressions for he coordinae ransformaions for scaling relaive o he origin are Scaling wih respec o a seleced fied posiion (,, ) can be represened wih he following ransformaion sequence: ) Translae he fied poin o he origin. 2) Scale he objec relaive o he coordinae origin. 3) Translae he fied poin back o is original posiion. Dep. of Compuer Science And Applicaions, SJCET, Palai
9 MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN OTHER TRANSFORMATIONS In addiion o ranslaion, roaion, and scaling, here are various addiional ransformaions ha are ofen useful in hree-dimensional graphics applicaions. Two of hese are reflecion and shear REFLECTIONS A hree-dimensional reflecion can be performed relaive o a seleced reflecion ais or wih respec o a seleced reflecion plane. In general, hree-dimensional reflecion marices are se up similarl o hose for wo dimensions. Reflecions relaive o a given ais are equivalen o 8 o roaions abou ha ais. Reflecions wih respec o a plane are equivalen o 8 o roaions in four-dimensional space. When he reflecion plane is a coordinae plane (eiher,, or ), we can hink of he ransformaion as a conversion beween Lef-handed and righ-handed ssems. An eample of a reflecion ha convers coordinae specificaions from a righhanded ssem o a lef-handed ssem (or vice versa) is shown in Fig This ransformaion changes he sign of he coordinaes, Leaving he and -coordinae values unchanged. The mari represenaion for his reflecion of poins relaive o he plane is given below Dep. of Compuer Science And Applicaions, SJCET, Palai 2
10 MODULE IV MCA - 3 COMPUTER GRAPHICS ADMN 29- (Fig: 4.3) Transformaion marices for invering and values are defined similarl, as reflecions relaive o he plane and plane, respecivel Reflecions abou oher planes can be obained as a combinaion of roaions and coordinae-plane reflecions SHEARS Shearing ransformaions can he used o modif objec shapes. The are also useful in hree-dimensional viewing for obaining general projecion ransformaions. In wo dimensions, we discussed ransformaion relaive o he or aes o produce disorions in he shapes of objecs. In hree dimensions, we can also generae shears relaive o he ais. As an eample of hree-dimensional shearing he following ransformaion produces a -ais shear: (Fig: 4.4) Parameers a and b can be assigned an real values. The effec of his ransformaion mari is o aler - and -coordinae values b an amoun ha is proporional o he value, while leaving he coordinae unchanged. Boundaries of planes ha are perpendicular o he ais are hus shifed b an amoun proporional o. An eample of he effec of his shearing mari on a uni cube is shown in Fig. 4-4, for shearing values a = b =. Shearing marices for he ais and ais are defined similarl. Dep. of Compuer Science And Applicaions, SJCET, Palai 3
CENG 477 Introduction to Computer Graphics. Modeling Transformations
CENG 477 Inroducion o Compuer Graphics Modeling Transformaions Modeling Transformaions Model coordinaes o World coordinaes: Model coordinaes: All shapes wih heir local coordinaes and sies. world World
More informationGeometry Transformation
Geomer Transformaion Januar 26 Prof. Gar Wang Dep. of Mechanical and Manufacuring Engineering Universi of Manioba Wh geomer ransformaion? Beer undersanding of he design Communicaion wih cusomers Generaing
More informationM y. Image Warping. Targil 7 : Image Warping. Image Warping. 2D Geometric Transformations. image filtering: change range of image g(x) = T(f(x))
Hebrew Universi Image Processing - 6 Image Warping Hebrew Universi Image Processing - 6 argil 7 : Image Warping D Geomeric ransormaions hp://www.jere-marin.com Man slides rom Seve Seiz and Aleei Eros Image
More informationSystems & Biomedical Engineering Department. Transformation
Sem & Biomedical Engineering Deparmen SBE 36B: Compuer Sem III Compuer Graphic Tranformaion Dr. Aman Eldeib Spring 28 Tranformaion Tranformaion i a fundamenal corner one of compuer graphic and i a cenral
More informationCS 428: Fall Introduction to. Geometric Transformations (continued) Andrew Nealen, Rutgers, /20/2010 1
CS 428: Fall 2 Inroducion o Compuer Graphic Geomeric Tranformaion (coninued) Andrew Nealen, Ruger, 2 9/2/2 Tranlaion Tranlaion are affine ranformaion The linear par i he ideni mari The 44 mari for he ranlaion
More informationSTEREO PLANE MATCHING TECHNIQUE
STEREO PLANE MATCHING TECHNIQUE Commission III KEY WORDS: Sereo Maching, Surface Modeling, Projecive Transformaion, Homography ABSTRACT: This paper presens a new ype of sereo maching algorihm called Sereo
More informationImage warping Li Zhang CS559
Wha is an image Image arping Li Zhang S559 We can hink of an image as a funcion, f: R 2 R: f(, ) gives he inensi a posiion (, ) defined over a recangle, ih a finie range: f: [a,b][c,d] [,] f Slides solen
More informationProjective geometry- 2D
Projecive geomer- D Acknowledgemens Marc Pollefes: for allowing e use of is ecellen slides on is opic p://www.cs.unc.edu/~marc/mvg/ Ricard Harle and Andrew Zisserman, "Muliple View Geomer in Compuer Vision"
More informationInteractive Graphical Systems HT2005
Ineracive Graphical Ssems HT25 Lesson 2 : Graphics Primer Sefan Seipel Sefan Seipel, Deparmen of Informaion Technolog, Uppsala Universi Ke issues of his lecure Represenaions of 3D models Repeiion of basic
More informationGauss-Jordan Algorithm
Gauss-Jordan Algorihm The Gauss-Jordan algorihm is a sep by sep procedure for solving a sysem of linear equaions which may conain any number of variables and any number of equaions. The algorihm is carried
More informationSection 2. Mirrors and Prism Systems
Secion 2 Mirrors and Prism Sysems 2-1 Plane Mirrors Plane mirrors are used o: Produce a deviaion Fold he opical pah Change he image pariy Each ray from he objec poin obeys he law of reflecion a he mirror
More informationCAMERA CALIBRATION BY REGISTRATION STEREO RECONSTRUCTION TO 3D MODEL
CAMERA CALIBRATION BY REGISTRATION STEREO RECONSTRUCTION TO 3D MODEL Klečka Jan Docoral Degree Programme (1), FEEC BUT E-mail: xkleck01@sud.feec.vubr.cz Supervised by: Horák Karel E-mail: horak@feec.vubr.cz
More informationEECS 487: Interactive Computer Graphics
EECS 487: Ineracive Compuer Graphics Lecure 7: B-splines curves Raional Bézier and NURBS Cubic Splines A represenaion of cubic spline consiss of: four conrol poins (why four?) hese are compleely user specified
More informationImage warping/morphing
Image arping/morphing Image arping Digial Visual Effecs Yung-Yu Chuang ih slides b Richard Szeliski, Seve Seiz, Tom Funkhouser and leei Efros Image formaion Sampling and quanizaion B Wha is an image We
More informationChapter Six Chapter Six
Chaper Si Chaper Si 0 CHAPTER SIX ConcepTess and Answers and Commens for Secion.. Which of he following graphs (a) (d) could represen an aniderivaive of he funcion shown in Figure.? Figure. (a) (b) (c)
More informationPoint Cloud Representation of 3D Shape for Laser- Plasma Scanning 3D Display
Poin Cloud Represenaion of 3D Shape for Laser- Plasma Scanning 3D Displa Hiroo Ishikawa and Hideo Saio Keio Universi E-mail {hiroo, saio}@ozawa.ics.keio.ac.jp Absrac- In his paper, a mehod of represening
More informationNEWTON S SECOND LAW OF MOTION
Course and Secion Dae Names NEWTON S SECOND LAW OF MOTION The acceleraion of an objec is defined as he rae of change of elociy. If he elociy changes by an amoun in a ime, hen he aerage acceleraion during
More informationProjection & Interaction
Projecion & Ineracion Algebra of projecion Canonical viewing volume rackball inerface ransform Hierarchies Preview of Assignmen #2 Lecure 8 Comp 236 Spring 25 Projecions Our lives are grealy simplified
More informationMOTION DETECTORS GRAPH MATCHING LAB PRE-LAB QUESTIONS
NME: TE: LOK: MOTION ETETORS GRPH MTHING L PRE-L QUESTIONS 1. Read he insrucions, and answer he following quesions. Make sure you resae he quesion so I don hae o read he quesion o undersand he answer..
More informationgeometric transformations
geomeric ranformaion comuer grahic ranform 28 fabio ellacini linear algebra review marice noaion baic oeraion mari-vecor mulilicaion comuer grahic ranform 28 fabio ellacini 2 marice noaion for marice and
More informationA METHOD OF MODELING DEFORMATION OF AN OBJECT EMPLOYING SURROUNDING VIDEO CAMERAS
A METHOD OF MODELING DEFORMATION OF AN OBJECT EMLOYING SURROUNDING IDEO CAMERAS Joo Kooi TAN, Seiji ISHIKAWA Deparmen of Mechanical and Conrol Engineering Kushu Insiue of Technolog, Japan ehelan@is.cnl.kuech.ac.jp,
More informationShortest Path Algorithms. Lecture I: Shortest Path Algorithms. Example. Graphs and Matrices. Setting: Dr Kieran T. Herley.
Shores Pah Algorihms Background Seing: Lecure I: Shores Pah Algorihms Dr Kieran T. Herle Deparmen of Compuer Science Universi College Cork Ocober 201 direced graph, real edge weighs Le he lengh of a pah
More informationAML710 CAD LECTURE 11 SPACE CURVES. Space Curves Intrinsic properties Synthetic curves
AML7 CAD LECTURE Space Curves Inrinsic properies Synheic curves A curve which may pass hrough any region of hreedimensional space, as conrased o a plane curve which mus lie on a single plane. Space curves
More informationA Matching Algorithm for Content-Based Image Retrieval
A Maching Algorihm for Conen-Based Image Rerieval Sue J. Cho Deparmen of Compuer Science Seoul Naional Universiy Seoul, Korea Absrac Conen-based image rerieval sysem rerieves an image from a daabase using
More informationImplementing Ray Casting in Tetrahedral Meshes with Programmable Graphics Hardware (Technical Report)
Implemening Ray Casing in Terahedral Meshes wih Programmable Graphics Hardware (Technical Repor) Marin Kraus, Thomas Erl March 28, 2002 1 Inroducion Alhough cell-projecion, e.g., [3, 2], and resampling,
More informationDesign Alternatives for a Thin Lens Spatial Integrator Array
Egyp. J. Solids, Vol. (7), No. (), (004) 75 Design Alernaives for a Thin Lens Spaial Inegraor Array Hala Kamal *, Daniel V azquez and Javier Alda and E. Bernabeu Opics Deparmen. Universiy Compluense of
More informationRay Casting. Outline. Outline in Code
Foundaions of ompuer Graphics Online Lecure 10: Ray Tracing 2 Nus and ols amera Ray asing Ravi Ramamoorhi Ouline amera Ray asing (choose ray direcions) Ray-objec inersecions Ray-racing ransformed objecs
More informationEffects needed for Realism. Ray Tracing. Ray Tracing: History. Outline. Foundations of Computer Graphics (Fall 2012)
Foundaions of ompuer Graphics (Fall 2012) S 184, Lecure 16: Ray Tracing hp://ins.eecs.berkeley.edu/~cs184 Effecs needed for Realism (Sof) Shadows Reflecions (Mirrors and Glossy) Transparency (Waer, Glass)
More information1.4 Application Separable Equations and the Logistic Equation
1.4 Applicaion Separable Equaions and he Logisic Equaion If a separable differenial equaion is wrien in he form f ( y) dy= g( x) dx, hen is general soluion can be wrien in he form f ( y ) dy = g ( x )
More informationA Principled Approach to. MILP Modeling. Columbia University, August Carnegie Mellon University. Workshop on MIP. John Hooker.
Slide A Principled Approach o MILP Modeling John Hooer Carnegie Mellon Universiy Worshop on MIP Columbia Universiy, Augus 008 Proposal MILP modeling is an ar, bu i need no be unprincipled. Slide Proposal
More informationComputer representations of piecewise
Edior: Gabriel Taubin Inroducion o Geomeric Processing hrough Opimizaion Gabriel Taubin Brown Universiy Compuer represenaions o piecewise smooh suraces have become vial echnologies in areas ranging rom
More information4. Minimax and planning problems
CS/ECE/ISyE 524 Inroducion o Opimizaion Spring 2017 18 4. Minima and planning problems ˆ Opimizing piecewise linear funcions ˆ Minima problems ˆ Eample: Chebyshev cener ˆ Muli-period planning problems
More informationTraditional Rendering (Ray Tracing and Radiosity)
Tradiional Rendering (Ray Tracing and Radiosiy) CS 517 Fall 2002 Compuer Science Cornell Universiy Bidirecional Reflecance (BRDF) λ direcional diffuse specular θ uniform diffuse τ σ BRDF Bidirecional Reflecance
More informationScattering at an Interface: Normal Incidence
Course Insrucor Dr. Raymond C. Rumpf Office: A 337 Phone: (915) 747 6958 Mail: rcrumpf@uep.edu 4347 Applied lecromagneics Topic 3f Scaering a an Inerface: Normal Incidence Scaering These Normal noes Incidence
More informationReinforcement Learning by Policy Improvement. Making Use of Experiences of The Other Tasks. Hajime Kimura and Shigenobu Kobayashi
Reinforcemen Learning by Policy Improvemen Making Use of Experiences of The Oher Tasks Hajime Kimura and Shigenobu Kobayashi Tokyo Insiue of Technology, JAPAN genfe.dis.iech.ac.jp, kobayasidis.iech.ac.jp
More information3-D Object Modeling and Recognition for Telerobotic Manipulation
Research Showcase @ CMU Roboics Insiue School of Compuer Science 1995 3-D Objec Modeling and Recogniion for Teleroboic Manipulaion Andrew Johnson Parick Leger Regis Hoffman Marial Heber James Osborn Follow
More informationFill in the following table for the functions shown below.
By: Carl H. Durney and Neil E. Coer Example 1 EX: Fill in he following able for he funcions shown below. he funcion is odd he funcion is even he funcion has shif-flip symmery he funcion has quarer-wave
More informationEngineering Mathematics 2018
Engineering Mahemaics 08 SUBJET NAME : Mahemaics II SUBJET ODE : MA65 MATERIAL NAME : Par A quesions REGULATION : R03 UPDATED ON : November 06 TEXTBOOK FOR REFERENE To buy he book visi : Sri Hariganesh
More informationVideo Content Description Using Fuzzy Spatio-Temporal Relations
Proceedings of he 4s Hawaii Inernaional Conference on Sysem Sciences - 008 Video Conen Descripion Using Fuzzy Spaio-Temporal Relaions rchana M. Rajurkar *, R.C. Joshi and Sananu Chaudhary 3 Dep of Compuer
More informationImage Content Representation
Image Conen Represenaion Represenaion for curves and shapes regions relaionships beween regions E.G.M. Perakis Image Represenaion & Recogniion 1 Reliable Represenaion Uniqueness: mus uniquely specify an
More informationMATH Differential Equations September 15, 2008 Project 1, Fall 2008 Due: September 24, 2008
MATH 5 - Differenial Equaions Sepember 15, 8 Projec 1, Fall 8 Due: Sepember 4, 8 Lab 1.3 - Logisics Populaion Models wih Harvesing For his projec we consider lab 1.3 of Differenial Equaions pages 146 o
More informationEXPERIMENTAL RESULTS GOT WITH THE OMNIDIRECTIONAL VISION SENSOR: SYCLOP
EXERIENTAL RESULTS GOT WITH THE ONIDIRECTIONAL ISION SENSOR: SYCLO Eric BRASSART, Lauren DELAHOCHE, Cyril CAUCHOIS, Cyril DROCOURT, Claude EGARD, El usapha OUADDIB CREA (Cenre de Roboique d Elecroechnique
More informationTHE micro-lens array (MLA) based light field cameras,
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL., NO., A Generic Muli-Projecion-Cener Model and Calibraion Mehod for Ligh Field Cameras Qi hang, Chunping hang, Jinbo Ling, Qing Wang,
More informationProbabilistic Detection and Tracking of Motion Discontinuities
Probabilisic Deecion and Tracking of Moion Disconinuiies Michael J. Black David J. Flee Xerox Palo Alo Research Cener 3333 Coyoe Hill Road Palo Alo, CA 94304 fblack,fleeg@parc.xerox.com hp://www.parc.xerox.com/fblack,fleeg/
More informationLAMP: 3D Layered, Adaptive-resolution and Multiperspective Panorama - a New Scene Representation
Submission o Special Issue of CVIU on Model-based and Image-based 3D Scene Represenaion for Ineracive Visualizaion LAMP: 3D Layered, Adapive-resoluion and Muliperspecive Panorama - a New Scene Represenaion
More informationAn Improved Square-Root Nyquist Shaping Filter
An Improved Square-Roo Nyquis Shaping Filer fred harris San Diego Sae Universiy fred.harris@sdsu.edu Sridhar Seshagiri San Diego Sae Universiy Seshigar.@engineering.sdsu.edu Chris Dick Xilinx Corp. chris.dick@xilinx.com
More informationImage segmentation. Motivation. Objective. Definitions. A classification of segmentation techniques. Assumptions for thresholding
Moivaion Image segmenaion Which pixels belong o he same objec in an image/video sequence? (spaial segmenaion) Which frames belong o he same video sho? (emporal segmenaion) Which frames belong o he same
More informationIn Proceedings of CVPR '96. Structure and Motion of Curved 3D Objects from. using these methods [12].
In Proceedings of CVPR '96 Srucure and Moion of Curved 3D Objecs from Monocular Silhouees B Vijayakumar David J Kriegman Dep of Elecrical Engineering Yale Universiy New Haven, CT 652-8267 Jean Ponce Compuer
More informationMotion Estimation of a Moving Range Sensor by Image Sequences and Distorted Range Data
Moion Esimaion of a Moving Range Sensor by Image Sequences and Disored Range Daa Asuhiko Banno, Kazuhide Hasegawa and Kasushi Ikeuchi Insiue of Indusrial Science Universiy of Tokyo 4-6-1 Komaba, Meguro-ku,
More informationRao-Blackwellized Particle Filtering for Probing-Based 6-DOF Localization in Robotic Assembly
MITSUBISHI ELECTRIC RESEARCH LABORATORIES hp://www.merl.com Rao-Blackwellized Paricle Filering for Probing-Based 6-DOF Localizaion in Roboic Assembly Yuichi Taguchi, Tim Marks, Haruhisa Okuda TR1-8 June
More informationCoded Caching with Multiple File Requests
Coded Caching wih Muliple File Requess Yi-Peng Wei Sennur Ulukus Deparmen of Elecrical and Compuer Engineering Universiy of Maryland College Park, MD 20742 ypwei@umd.edu ulukus@umd.edu Absrac We sudy a
More informationVirtual Recovery of Excavated Archaeological Finds
Virual Recovery of Excavaed Archaeological Finds Jiang Yu ZHENG, Zhong Li ZHANG*, Norihiro ABE Kyushu Insiue of Technology, Iizuka, Fukuoka 820, Japan *Museum of he Terra-Coa Warrlors and Horses, Lin Tong,
More informationWhat and Why Transformations?
2D transformations What and Wh Transformations? What? : The geometrical changes of an object from a current state to modified state. Changing an object s position (translation), orientation (rotation)
More informationTOOTH ALIGNMENT OF THE DENTAL CAST USING 3D THIN PLATE SPLINE
TOOTH ALIGMET OF THE DETAL CAST USIG 3D THI LATE SLIE Chanjira Sinhanaohin, Wisaru Bholsihi, Wichi Tharanon aional Science and Technolog Developmen Agenc (STDA 111 Thailand Science ark, hahon-yohin d,
More informationEfficient Region Tracking With Parametric Models of Geometry and Illumination
EEE TRANSACTONS ON PATTERN ANALYSS AND MACHNE NTELLGENCE, VOL. 2, NO. 1, OCTOBER 1998 1 Efficien Region Tracking Wih Parameric Models of Geomery and lluminaion Gregory D. Hager, Member, EEE, and Peer N.
More informationProceeding of the 6 th International Symposium on Artificial Intelligence and Robotics & Automation in Space: i-sairas 2001, Canadian Space Agency,
Proceeding of he 6 h Inernaional Symposium on Arificial Inelligence and Roboics & Auomaion in Space: i-sairas 00, Canadian Space Agency, S-Huber, Quebec, Canada, June 8-, 00. Muli-resoluion Mapping Using
More informationLandmarks: A New Model for Similarity-Based Pattern Querying in Time Series Databases
Lmarks: A New Model for Similariy-Based Paern Querying in Time Series Daabases Chang-Shing Perng Haixun Wang Sylvia R. Zhang D. So Parker perng@cs.ucla.edu hxwang@cs.ucla.edu Sylvia Zhang@cle.com so@cs.ucla.edu
More informationAlgorithm for image reconstruction in multi-slice helical CT
Algorihm for image reconsrucion in muli-slice helical CT Kasuyuki Taguchi a) and Hiroshi Aradae Medical Engineering Laboraory, Toshiba Corporaion, 1385 Shimoishigami, Oawara, Tochigi 324-855, Japan Received
More informationMARSS Reference Sheet
MARSS Reference Shee The defaul MARSS model (form="marxss") is wrien as follows: x = B x 1 + u + C c + w where w MVN( Q ) y = Z x + a + D d + v where v MVN( R ) x 1 MVN(π Λ) or x MVN(π Λ) c and d are inpus
More informationOcclusion-Free Hand Motion Tracking by Multiple Cameras and Particle Filtering with Prediction
58 IJCSNS Inernaional Journal of Compuer Science and Nework Securiy, VOL.6 No.10, Ocober 006 Occlusion-Free Hand Moion Tracking by Muliple Cameras and Paricle Filering wih Predicion Makoo Kao, and Gang
More informationX-Splines : A Spline Model Designed for the End-User
X-Splines : A Spline Model Designed for he End-User Carole Blanc Chrisophe Schlic LaBRI 1 cours de la libéraion, 40 alence (France) [blancjschlic]@labri.u-bordeaux.fr Absrac his paper presens a new model
More informationSpline Curves. Color Interpolation. Normal Interpolation. Last Time? Today. glshademodel (GL_SMOOTH); Adjacency Data Structures. Mesh Simplification
Las Time? Adjacency Daa Srucures Spline Curves Geomeric & opologic informaion Dynamic allocaion Efficiency of access Mesh Simplificaion edge collapse/verex spli geomorphs progressive ransmission view-dependen
More informationA Hierarchical Object Recognition System Based on Multi-scale Principal Curvature Regions
A Hierarchical Objec Recogniion Sysem Based on Muli-scale Principal Curvaure Regions Wei Zhang, Hongli Deng, Thomas G Dieerich and Eric N Morensen School of Elecrical Engineering and Compuer Science Oregon
More informationSegmentation by Level Sets and Symmetry
Segmenaion by Level Ses and Symmery Tammy Riklin-Raviv Nahum Kiryai Nir Sochen Tel Aviv Universiy, Tel Aviv 69978, Israel ammy@eng.au.ac.il nk@eng.au.ac.il sochen@pos.au.ac.il Absrac Shape symmery is an
More informationSTRING DESCRIPTIONS OF DATA FOR DISPLAY*
SLAC-PUB-383 January 1968 STRING DESCRIPTIONS OF DATA FOR DISPLAY* J. E. George and W. F. Miller Compuer Science Deparmen and Sanford Linear Acceleraor Cener Sanford Universiy Sanford, California Absrac
More informationMulti-Viewpoint Video Coding with MPEG-2 Compatibility. Belle L. Tseng and Dimitris Anastassiou. Columbia University New York, N.Y.
Muli-Viewpoin Video oding wih MPEG-2 ompaibiliy Belle L. Tseng and Dimiris Anasassiou olumbia niversiy New York, N.Y. 10027 SA Absrac An ecien video coding scheme is presened as an exension of he MPEG-2
More informationFLOW VISUALIZATION USING MOVING TEXTURES * Nelson Max Lawrence Livermore National Laboratory Livermore, California
FLOW VISUALIZATION USING MOVING TEXTURES * Nelson Max Lawrence Livermore Naional Laboraor Livermore, California Barr Becker Lawrence Livermore Naional Laboraor Livermore, California SUMMARY We presen a
More informationLearning Topological Image Transforms Using Cellular Simultaneous Recurrent Networks
Proceedings of Inernaional Join Conference on Neural Neworks Dallas Texas USA Augus 4-9 013 Learning Topological Image Transforms Using Cellular Simulaneous Recurren Neworks J. Keih Anderson Deparmen of
More informationAn Adaptive Spatial Depth Filter for 3D Rendering IP
JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE, VOL.3, NO. 4, DECEMBER, 23 175 An Adapive Spaial Deph Filer for 3D Rendering IP Chang-Hyo Yu and Lee-Sup Kim Absrac In his paper, we presen a new mehod
More informationReal-Time Avatar Animation Steered by Live Body Motion
Real-Time Avaar Animaion Seered by Live Body Moion Oliver Schreer, Ralf Tanger, Peer Eiser, Peer Kauff, Bernhard Kaspar, and Roman Engler 3 Fraunhofer Insiue for Telecommunicaions/Heinrich-Herz-Insiu,
More informationRobust 3D Visual Tracking Using Particle Filtering on the SE(3) Group
Robus 3D Visual Tracking Using Paricle Filering on he SE(3) Group Changhyun Choi and Henrik I. Chrisensen Roboics & Inelligen Machines, College of Compuing Georgia Insiue of Technology Alana, GA 3332,
More informationPage 1. News. Compositing, Clipping, Curves. Week 3, Thu May 26. Schedule Change. Homework 1 Common Mistakes. Midterm Logistics.
Universiy of Briish Columbia CPSC 4 Compuer Graphics May-June 5 Tamara Munzner Composiing, Clipping, Curves Week, Thu May 6 hp://www.ugrad.cs.ubc.ca/~cs4/vmay5 News era lab coverage: Mon -, Wed -4 P demo
More informationA Fast Stereo-Based Multi-Person Tracking using an Approximated Likelihood Map for Overlapping Silhouette Templates
A Fas Sereo-Based Muli-Person Tracking using an Approximaed Likelihood Map for Overlapping Silhouee Templaes Junji Saake Jun Miura Deparmen of Compuer Science and Engineering Toyohashi Universiy of Technology
More informationIt is easier to visualize plotting the curves of cos x and e x separately: > plot({cos(x),exp(x)},x = -5*Pi..Pi,y = );
Mah 467 Homework Se : some soluions > wih(deools): wih(plos): Warning, he name changecoords has been redefined Problem :..7 Find he fixed poins, deermine heir sabiliy, for x( ) = cos x e x > plo(cos(x)
More informationSalt-dome detection using the Gradient of Texture. Initialization Point. Region Morphological
Deecion of Sal-dome Boundar Surfaces in Migraed Seismic Volumes Using Gradien of Teures Muhammad A. Shafiq, Zhen Wang, Asjad Amin, Tamir Hegaz, Mohamed Deriche, and Ghassan AlRegib Cener for Energ and
More informationMichiel Helder and Marielle C.T.A Geurts. Hoofdkantoor PTT Post / Dutch Postal Services Headquarters
SHORT TERM PREDICTIONS A MONITORING SYSTEM by Michiel Helder and Marielle C.T.A Geurs Hoofdkanoor PTT Pos / Duch Posal Services Headquarers Keywords macro ime series shor erm predicions ARIMA-models faciliy
More informationGeodesic, Flow Front and Voronoi Diagram
11 Geodesic, Flow Fron and Voronoi Diagram C. K. Au Nannag Technological Uniersi, mckau@nu.edu.sg ABSTRACT Geodesics and flow frons are orhogonal o each oher. These wo ses consiue he space ime funcion
More informationChapter 4 Sequential Instructions
Chaper 4 Sequenial Insrucions The sequenial insrucions of FBs-PLC shown in his chaper are also lised in secion 3.. Please refer o Chaper, "PLC Ladder diagram and he Coding rules of Mnemonic insrucion",
More informationMOTION TRACKING is a fundamental capability that
TECHNICAL REPORT CRES-05-008, CENTER FOR ROBOTICS AND EMBEDDED SYSTEMS, UNIVERSITY OF SOUTHERN CALIFORNIA 1 Real-ime Moion Tracking from a Mobile Robo Boyoon Jung, Suden Member, IEEE, Gaurav S. Sukhame,
More informationVisual Perception as Bayesian Inference. David J Fleet. University of Toronto
Visual Percepion as Bayesian Inference David J Flee Universiy of Torono Basic rules of probabiliy sum rule (for muually exclusive a ): produc rule (condiioning): independence (def n ): Bayes rule: marginalizaion:
More informationEvaluation and Improvement of Region-based Motion Segmentation
Evaluaion and Improvemen of Region-based Moion Segmenaion Mark Ross Universiy Koblenz-Landau, Insiue of Compuaional Visualisics, Universiässraße 1, 56070 Koblenz, Germany Email: ross@uni-koblenz.de Absrac
More informationDynamic Depth Recovery from Multiple Synchronized Video Streams 1
Dynamic Deph Recoery from Muliple ynchronized Video reams Hai ao, Harpree. awhney, and Rakesh Kumar Deparmen of Compuer Engineering arnoff Corporaion Uniersiy of California a ana Cruz Washingon Road ana
More informationparametric spline curves
arameric sline curves comuer grahics arameric curves 9 fabio ellacini curves used in many conexs fons animaion ahs shae modeling differen reresenaion imlici curves arameric curves mosly used comuer grahics
More informationRobust Multi-view Face Detection Using Error Correcting Output Codes
Robus Muli-view Face Deecion Using Error Correcing Oupu Codes Hongming Zhang,2, Wen GaoP P, Xilin Chen 2, Shiguang Shan 2, and Debin Zhao Deparmen of Compuer Science and Engineering, Harbin Insiue of Technolog
More informationRay Tracing II. Improving Raytracing Speed. Improving Computational Complexity. Raytracing Computational Complexity
Ra Tracing II Iproving Raracing Speed Copuer Graphics Ra Tracing II 2005 Fabio Pellacini 1 Copuer Graphics Ra Tracing II 2005 Fabio Pellacini 2 Raracing Copuaional Coplei ra-scene inersecion is epensive
More informationFIELD PROGRAMMABLE GATE ARRAY (FPGA) AS A NEW APPROACH TO IMPLEMENT THE CHAOTIC GENERATORS
FIELD PROGRAMMABLE GATE ARRAY (FPGA) AS A NEW APPROACH TO IMPLEMENT THE CHAOTIC GENERATORS Mohammed A. Aseeri and M. I. Sobhy Deparmen of Elecronics, The Universiy of Ken a Canerbury Canerbury, Ken, CT2
More informationA non-stationary uniform tension controlled interpolating 4-point scheme reproducing conics
A non-saionary uniform ension conrolled inerpolaing 4-poin scheme reproducing conics C. Beccari a, G. Casciola b, L. Romani b, a Deparmen of Pure and Applied Mahemaics, Universiy of Padova, Via G. Belzoni
More informationAUTOMATIC 3D FACE REGISTRATION WITHOUT INITIALIZATION
Chaper 3 AUTOMATIC 3D FACE REGISTRATION WITHOUT INITIALIZATION A. Koschan, V. R. Ayyagari, F. Boughorbel, and M. A. Abidi Imaging, Roboics, and Inelligen Sysems Laboraory, The Universiy of Tennessee, 334
More informationAn Accelerated ISAF Algorithm with the Fast Mapping Strategy
528 JOURNAL OF COMPUTERS, VOL. 7, NO. 2, FEBRUARY 202 An Acceleraed ISAF Algorihm wih he Fas Mapping Sraegy Gongming Wang Insiue of Compuing Technology, Chinese Academy of Sciences, Beijing, China. 0090
More informationDefinition and examples of time series
Definiion and examples of ime series A ime series is a sequence of daa poins being recorded a specific imes. Formally, le,,p be a probabiliy space, and T an index se. A real valued sochasic process is
More informationHermite Curves. Jim Armstrong Singularity November 2005
TechNoe TN-5- Herie Curves Ji Arsrong Singulariy Noveer 5 This is he second in a series of TechNoes on he sujec of applied curve aheaics in Adoe Flash TM. Each TechNoe provides a aheaical foundaion for
More informationImage Based Computer-Aided Manufacturing Technology
Sensors & Transducers 03 by IFSA hp://www.sensorsporal.com Image Based Compuer-Aided Manufacuring Technology Zhanqi HU Xiaoqin ZHANG Jinze LI Wei LI College of Mechanical Engineering Yanshan Universiy
More informationRobust Segmentation and Tracking of Colored Objects in Video
IEEE TRANSACTIONS ON CSVT, VOL. 4, NO. 6, 2004 Robus Segmenaion and Tracking of Colored Objecs in Video Theo Gevers, member, IEEE Absrac Segmening and racking of objecs in video is of grea imporance for
More informationLearning in Games via Opponent Strategy Estimation and Policy Search
Learning in Games via Opponen Sraegy Esimaion and Policy Search Yavar Naddaf Deparmen of Compuer Science Universiy of Briish Columbia Vancouver, BC yavar@naddaf.name Nando de Freias (Supervisor) Deparmen
More information1 œ DRUM SET KEY. 8 Odd Meter Clave Conor Guilfoyle. Cowbell (neck) Cymbal. Hi-hat. Floor tom (shell) Clave block. Cowbell (mouth) Hi tom.
DRUM SET KEY Hi-ha Cmbal Clave block Cowbell (mouh) 0 Cowbell (neck) Floor om (shell) Hi om Mid om Snare Floor om Snare cross sick or clave block Bass drum Hi-ha wih foo 8 Odd Meer Clave Conor Guilfole
More informationWiley Plus. Assignment 1 is online:
Wile Plus Assignmen 1 is online: 6 problems from chapers and 3 1D and D Kinemaics Due Monda Ocober 5 Before 11 pm! Chaper II: Kinemaics In One Dimension Displacemen Speed and Veloci Acceleraion Equaions
More information4 Error Control. 4.1 Issues with Reliable Protocols
4 Error Conrol Jus abou all communicaion sysems aemp o ensure ha he daa ges o he oher end of he link wihou errors. Since i s impossible o build an error-free physical layer (alhough some shor links can
More information4. Two Dimensional Transformations
4. Two Dimensional Transformations CS362 Introduction to Computer Graphics Helena Wong, 2 In man applications, changes in orientations, sizes, and shapes are accomplished with geometric transformations
More informationGeometric Calibration of Ziyuan-3 Three-Line Cameras Using Ground Control Lines
Geomeric Calibraion of Ziyuan-3 Three-Line Cameras Using Ground Conrol Lines Jinshan Cao, Xiuxiao Yuan, Yi Fang, and Jianya Gong Absrac Owing o he large biases of laboraory-calibraed imaging parameers,
More informationComputer Graphics. Geometric Transformations
Contents coordinate sstems scalar values, points, vectors, matrices right-handed and left-handed coordinate sstems mathematical foundations transformations mathematical descriptions of geometric changes,
More information