High-Quality Unstructured Volume Rendering on the PC Platform

Size: px
Start display at page:

Download "High-Quality Unstructured Volume Rendering on the PC Platform"

Transcription

1 High-Quaity Unstructured Voume Rendering on the PC Patorm Stean Guthe, Wogang Strasser WSI/GRIS University o Tuebingen Stean Röttger, Andreas Schieber, Thomas Ert II/VIS University o Stuttgart Hardware Workshop 22

2 Overview Introduction Motivation Ce Projection High Resoution Ray Integra Opacity Reconstruction Chromaticity Reconstruction Hardware Acceerated Pre-Integration Resuts & Concusion 2/32

3 Introduction

4 Motivation Tetrahedra Meshes Common or numerica simuations Adaptive resoution Straight orward mutiresoution agorithms Genera purpose hardware Widey avaiabe Fast poygona rendering Fexibe ragment shading or recent generations Fast deveopment o uture generations Cheap compared to specia purpose hardware 4/32

5 Ce Projection Projected Tetrahedra (PT) Agorithm Shirey and Tuchman 9 Cassiy tetrahedra based on proie o projection Spit tetrahedra into 3 or 4 trianges Cass 21b 1a 5/32

6 Ce Projection Projected Tetrahedra (PT) Agorithm Render projected proies Chromaticity vector κ =κ ( ( x, y, z) ) Scaar optica density ρ = ρ ( ( x, y, z) ) Resuting ray integra C α S ( x) = S + ( S S ) ( S, S, ) ( S, S, ) b b = = e t ρ ( S ( u) ) du 1 e x κ SS b ( S ( t) ) ρ( S ( t) ) ρ b ( S ( t )) dt dt 6/32

7 Ray Integra

8 Opacity Reconstruction Approximation o opacity Corresponding portion o the ray integra S = e α 1 (, S, ) b ( S ( t )) ρ dt Origina approximation Cacuate correct vaues or vertices Interpoate ineary between vertices Improvement by Stein et a. 94 Cacuate average extinction coeicient Use texture map or exponentia ookup α ρ ( ρ) = 1 e Linear opacity or piecewise inear (HIAC 98) ρ 8/32

9 Opacity Reconstruction Approximation o opacity Corresponding portion o the ray integra S = e α 1 (, S, ) b ( S ( t )) ρ dt Further improvements 2D texture map or ookup o average extinction 1D dependent texture ookup ρ ( ) ( S, S ) ρ S ( t) α b 1 = ρ ( ρ) = 1 e No restriction to inear opacity dt 9/32

10 Opacity Reconstruction Approximation o opacity (GeForce 4) Texture setup unit coordinates S, S b RGB chrom. (RGA) 1 A ( ( t) ) ρ S dt 1,, 1 e ρ Pixe shader ps.1.3 de c, 1, 1,, tex t // oad chromaticity and density texdp3 t1, t // dependent ookup rp r.rgb, c, t, t.a // extract chromaticity... +mov r.a, t1.a // and apha or ina coor 1/32

11 Opacity Reconstruction Approximation o opacity (Radeon 85) Texture setup unit coordinates S, S b RGB chromaticity 1 A ( ( t) ) ρ S dt 1,, 1 e ρ Pixe shader ps.1.4 texd r, t // oad chromaticity and density texcrd r1, t1 // pass into register mu r1, r.a, r1.b // mutipy density and phase texpass r, r // transer chromaticity texd r1, r1 // dependent ookup mov r.a, r1.a // correct apha or ina coor 11/32

12 Chromaticity Reconstruction Approximation o chromaticity Corresponding portion o the ray integra C ρ ( S ( u) ) du, = e κ ρ ( S S, ) b Origina approximation t ( S ( t) ) ( S ( t) ) Cacuate correct vaues or vertices Interpoate ineary between vertices Improvement in HIAC 98 Cacuate vaues or sices through tetrahedra Texture ookup instead o inear interpoation Support o piecewise inear transer unctions dt 12/32

13 Chromaticity Reconstruction Approximation o chromaticity Corresponding portion o the ray integra C ρ ( S ( u) ) du, = e κ ρ ( S S, ) b t ( S ( t) ) ( S ( t) ) Improvement by Roettger et a. 3D texture or chromaticity and opacity Sow update o transer unction High memory requirements o 3D textures Accurate ony or sma tetrahedra due to imited resoution o pre-integration tabe dt 13/32

14 Chromaticity Reconstruction Approximation o chromaticity Corresponding portion o the ray integra C ρ ( S ( u) ) du, = e κ ρ ( S S, ) b Dierent approach t ( S ( t) ) ( S ( t) ) Higher order poynomias in Number o trianges equa to PT Ony 4 sices or cubic poynomias C Higher resoution tabe high image quaity Faster update o transer unction, b 1 e ρ ( S S, ) ( S ( t )) dt n i= i C i dt ( S, S ) b 14/32

15 Opacity Reconstruction Approximation o chromaticity (GeForce 4) Texture setup (B and A swapped or unit ) unit coordinates S, S b S, C S, S b - S b S, S b,, RGB ( S ) 2 S b ( ) 1 ( ) C, C S, S b - 1 A ( ( t) ) ρ S - 1 e ρ dt Additionay store in primary coor apha Distribution o dupicate vaues via vertex shader 15/32

16 Chromaticity Reconstruction Approximation o chromaticity (GeForce 4) Pixe shader ps.1.3 de c, 1, 1,, tex t // oad chromaticity and density tex t1 tex t2 texdp3 t3, t // dependent ookup rp r.rgb, c, t, t.a // extract chromaticity mad r.rgb, v.a, r, t1 // cacuate poynomia... mad r.rgb, v.a, r, t2 +mov r.a, t1.a // and get apha or ina coor 16/32

17 Opacity Reconstruction Approximation o chromaticity (Radeon 85) Texture setup unit coordinates S, S b S, S b S, S b S, S b S, S b,, RGB ( S ) 4 S b ( ) 3 ( ) 2 ( ) 1 ( ) C, C S, S b C S, S b C S, S b C S, S b Additionay store in primary coor apha - 1 A ( ( t) ) ρ S e ρ dt 17/32

18 Chromaticity Reconstruction Approximation o chromaticity (Radeon 85) Pixe shader ps.1.4 texd r, t // oad chromaticity and density texcrd r5, t5 // pass into register mu r5, r.a, r5.b // mutipy density and phase texd r1, t1 // oad other coeicients texd r2, t2 texd r3, t3 texd r4, t4 texd r5, r5 // dependent ookup mad r.rgb, v.a, r, r1 // cacuate poynomia... mad r.rgb, v.a, r, r2 mad r.rgb, v.a, r, r3 mad r.rgb, v.a, r, r4 +mov r.a, r1.a // and get apha or ina coor 18/32

19 Chromaticity Reconstruction Probems o this approach Limited precision o textures coud be a probem normaize coeicients Additiona vertex shader needed Optima approximation requires a east square it or chromaticity (ineasibe) Part o the three-dimensiona pre-integration tabe needs to be computed Interactive change o cassiication no onger possibe with sotware-ony cacuation o approximation textures 19/32

20 HW Acceeration

21 HW Acceerated Pre-Int. Hardware acceerated pre-integration Use bending capabiities o graphics card Construct pre-integration tabe sice by sice ( constant) Probems High error with ew bending operations High error with ots o bending operations Sow, due to arge amount o rame buer writes Accuracy o 8 bits too ow No probem with new oating point hardware 21/32

22 HW Acceerated Pre-Int. High accuracy pre-integration Use high interna precision o pixe shader Create pre-integration tabe using 12-bit vaues Perorm mutipe bending operations at once 4 bending operations in one step speedup o approximatey 2 Store high precision vaues in two 8-bit vaues Loose some instructions to combining and spitting high precision vaues No apha bending ping-pong rendering Separate passes or R,G and B 22/32

23 HW Acceerated Pre-Int. Comparison o sotware and hardware pre-integration Speedup o about 7% Reativey ow error hardware sotware dierence 8 23/32

24 HW Acceerated Pre-Int. HW acceerated pre-integration (Radeon 85) Pixe shader combine de c,.1968,,, // 1/256 mad r, r.ggaa, c.r, r.rrbb // combine vaues Use R and B or cacuations Mutipy resut by 8 during ast bending operation aster spit Pixe shader spit add_x8 r.ga, r_x2.rrbb, r_x2.rrbb // get ow bits mov_d8 r.rb, r.rrbb // get high bits 24/32

25 HW Acceerated Pre-Int. HW acceerated pre-integration (Radeon 85) ps.1.4 de c,.1968,,, // 1/256 texd r, t // previous data texd r1, t1 // 4 sampes texd r4, t4 mad r, r.ggaa, c.r, r.rrbb // combine vaues mad r1, r1.ggaa, c.r, r1.rrbb mad r2, r2.ggaa, c.r, r2.rrbb mad r3, r3.ggaa, c.r, r3.rrbb mad r4, r4.ggaa, c.r, r4.rrbb phase mad r1.rb, r, 1-r1.b, r1 // perorm bending mad r2.rb, r1, 1-r2.b, r2 mad r3.rb, r2, 1-r3.b, r3 mad_x8 r4.rb, r3, 1-r4.b, r4 add_x8 r.ga, r4_x2.rrbb, r4_x2.rrbb // get ow bits mov_d8 r.rb, r4.rrbb // get high bits 25/32

26 Resuts

27 Resuts Prototype (12,936 tetras) Buckyba (176,856 tetras) at ps at 2.46 ps 27/32

28 Resuts Bunt in (187,395 tetras) at 3.18 ps 28/32

29 Resuts Bonsai (538,937 tetras) Trumpet (1,567,755 tetras) at 1.2 ps at.48 ps 29/32

30 Video 3/32

31 Concusion Agorithm overview Dependent texture or opacity Poynomia approximation o chromaticity High resoution pre-integration tabe High quaity rendering 3 sices or quadratic approximation 5 sices or ourth order approximation Fast update whenever transer unction changes Number o trianges equa to origina PT agorithm Fast rendering 31/32

32 Concusion Migration to new graphics hardware HW pre-integration Foating point improves accuracy More bending steps at once even more perormance gain Image quaity wi be improved by oating point rame buer precision No dependent texture ookup due to exp-unction in pixe shader 32/32

33 Questions? 33/32

High-Quality Unstructured Volume Rendering on the PC Platform

High-Quality Unstructured Volume Rendering on the PC Platform Graphics Hardware (2002), pp. 1 8 Thomas Ert, Wofgang Heidrich, and Michae Doggett (Editors) High-Quaity Unstructured Voume Rendering on the PC Patform Stefan Guthe Stefan Roettger Andreas Schieber Wofgang

More information

A Two-Step Approach for Interactive Pre-Integrated Volume Rendering of Unstructured Grids

A Two-Step Approach for Interactive Pre-Integrated Volume Rendering of Unstructured Grids A Two-Step Approach for Interactive Pre-Integrated Voume Rendering of Unstructured Grids Stefan Roettger and Thomas Ert Visuaization and Interactive Systems Group University of Stuttgart Abstract In the

More information

Hardware-Accelerated Volume And Isosurface Rendering Based On Cell-Projection

Hardware-Accelerated Volume And Isosurface Rendering Based On Cell-Projection Hardware-Acceerated Voume And Isosurface Rendering Based On Ce-Projection Stefan Röttger, Martin Kraus, Thomas Ert Visuaization and Interactive Systems Group Universität Stuttgart, Germany Abstract We

More information

Smart Hardware-Accelerated Volume Rendering

Smart Hardware-Accelerated Volume Rendering Joint EUROGRAPHICS - IEEE TCVG Symposium on Visuaization (2003) G.-P. Bonneau, S. Hahmann, C. D. Hansen (Editors) Smart Hardware-Acceerated Voume Rendering Stefan Roettger 1, Stefan Guthe 2, Danie Weiskopf

More information

Approximate Volume Rendering for Curvilinear and Unstructured Grids by Hardware-Assisted Polyhedron Projection

Approximate Volume Rendering for Curvilinear and Unstructured Grids by Hardware-Assisted Polyhedron Projection Approximate Voume Rendering for Curviinear and Unstructured Grids by Hardware-Assisted Poyhedron Projection Neson Max, 1 Peter Wiiams, 1 Caudio Siva 2 1 Lawrence Livermore Nationa Laboratory 2 AT&T Labs-Research

More information

Sensitivity Analysis of Hopfield Neural Network in Classifying Natural RGB Color Space

Sensitivity Analysis of Hopfield Neural Network in Classifying Natural RGB Color Space Sensitivity Anaysis of Hopfied Neura Network in Cassifying Natura RGB Coor Space Department of Computer Science University of Sharjah UAE rsammouda@sharjah.ac.ae Abstract: - This paper presents a study

More information

Computer Graphics. - Shading & Texturing -

Computer Graphics. - Shading & Texturing - Computer Graphics - Shading & Texturing - Empirica BRDF Approximation Purey heuristic mode Initiay without units (vaues [0,1] r = r,a + r,d + r,s ( + r,m + r,t r,a : Ambient term Approximate indirect iumination

More information

Shading. Slides by Ulf Assarsson and Tomas Akenine-Möller Department of Computer Engineering Chalmers University of Technology

Shading. Slides by Ulf Assarsson and Tomas Akenine-Möller Department of Computer Engineering Chalmers University of Technology Shading Sides by Uf Assarsson and Tomas Akenine-Möer Department of Computer Engineering Chamers University of Technoogy Overview of today s ecture A simpe most basic rea-time ighting mode It is aso OpenGL

More information

Load Balancing by MPLS in Differentiated Services Networks

Load Balancing by MPLS in Differentiated Services Networks Load Baancing by MPLS in Differentiated Services Networks Riikka Susitaiva, Jorma Virtamo, and Samui Aato Networking Laboratory, Hesinki University of Technoogy P.O.Box 3000, FIN-02015 HUT, Finand {riikka.susitaiva,

More information

Nearest Neighbor Learning

Nearest Neighbor Learning Nearest Neighbor Learning Cassify based on oca simiarity Ranges from simpe nearest neighbor to case-based and anaogica reasoning Use oca information near the current query instance to decide the cassification

More information

Efficient method to design RF pulses for parallel excitation MRI using gridding and conjugate gradient

Efficient method to design RF pulses for parallel excitation MRI using gridding and conjugate gradient Origina rtice Efficient method to design RF puses for parae excitation MRI using gridding and conjugate gradient Shuo Feng, Jim Ji Department of Eectrica & Computer Engineering, Texas & M University, Texas,

More information

Computer Graphics (CS 543) Lecture 9b: Shadows and Shadow Maps. Prof Emmanuel Agu. Computer Science Dept. Worcester Polytechnic Institute (WPI)

Computer Graphics (CS 543) Lecture 9b: Shadows and Shadow Maps. Prof Emmanuel Agu. Computer Science Dept. Worcester Polytechnic Institute (WPI) Computer Graphics (CS 543) Lecture 9b: Shadows and Shadow Maps Prof Emmanue Agu Computer Science Dept. Worcester Poytechnic Institute (WPI) Introduction to Shadows Shadows give information on reative positions

More information

Lecture outline Graphics and Interaction Scan Converting Polygons and Lines. Inside or outside a polygon? Scan conversion.

Lecture outline Graphics and Interaction Scan Converting Polygons and Lines. Inside or outside a polygon? Scan conversion. Lecture outine 433-324 Graphics and Interaction Scan Converting Poygons and Lines Department of Computer Science and Software Engineering The Introduction Scan conversion Scan-ine agorithm Edge coherence

More information

On-Chip CNN Accelerator for Image Super-Resolution

On-Chip CNN Accelerator for Image Super-Resolution On-Chip CNN Acceerator for Image Super-Resoution Jung-Woo Chang and Suk-Ju Kang Dept. of Eectronic Engineering, Sogang University, Seou, South Korea {zwzang91, sjkang}@sogang.ac.kr ABSTRACT To impement

More information

Lecture Notes for Chapter 4 Part III. Introduction to Data Mining

Lecture Notes for Chapter 4 Part III. Introduction to Data Mining Data Mining Cassification: Basic Concepts, Decision Trees, and Mode Evauation Lecture Notes for Chapter 4 Part III Introduction to Data Mining by Tan, Steinbach, Kumar Adapted by Qiang Yang (2010) Tan,Steinbach,

More information

Optimization and Application of Support Vector Machine Based on SVM Algorithm Parameters

Optimization and Application of Support Vector Machine Based on SVM Algorithm Parameters Optimization and Appication of Support Vector Machine Based on SVM Agorithm Parameters YAN Hui-feng 1, WANG Wei-feng 1, LIU Jie 2 1 ChongQing University of Posts and Teecom 400065, China 2 Schoo Of Civi

More information

17.3 Surface Area of Pyramids and Cones

17.3 Surface Area of Pyramids and Cones Name Cass Date 17.3 Surface Area of Pyramids and Cones Essentia Question: How is the formua for the atera area of a reguar pyramid simiar to the formua for the atera area of a right cone? Expore G.11.C

More information

Design of IP Networks with End-to. to- End Performance Guarantees

Design of IP Networks with End-to. to- End Performance Guarantees Design of IP Networks with End-to to- End Performance Guarantees Irena Atov and Richard J. Harris* ( Swinburne University of Technoogy & *Massey University) Presentation Outine Introduction Mutiservice

More information

AN EVOLUTIONARY APPROACH TO OPTIMIZATION OF A LAYOUT CHART

AN EVOLUTIONARY APPROACH TO OPTIMIZATION OF A LAYOUT CHART 13 AN EVOLUTIONARY APPROACH TO OPTIMIZATION OF A LAYOUT CHART Eva Vona University of Ostrava, 30th dubna st. 22, Ostrava, Czech Repubic e-mai: Eva.Vona@osu.cz Abstract: This artice presents the use of

More information

A Fast Block Matching Algorithm Based on the Winner-Update Strategy

A Fast Block Matching Algorithm Based on the Winner-Update Strategy In Proceedings of the Fourth Asian Conference on Computer Vision, Taipei, Taiwan, Jan. 000, Voume, pages 977 98 A Fast Bock Matching Agorithm Based on the Winner-Update Strategy Yong-Sheng Chenyz Yi-Ping

More information

Extended Node-Arc Formulation for the K-Edge-Disjoint Hop-Constrained Network Design Problem

Extended Node-Arc Formulation for the K-Edge-Disjoint Hop-Constrained Network Design Problem Extended Node-Arc Formuation for the K-Edge-Disjoint Hop-Constrained Network Design Probem Quentin Botton Université cathoique de Louvain, Louvain Schoo of Management, (Begique) botton@poms.uc.ac.be Bernard

More information

A Comparison of a Second-Order versus a Fourth- Order Laplacian Operator in the Multigrid Algorithm

A Comparison of a Second-Order versus a Fourth- Order Laplacian Operator in the Multigrid Algorithm A Comparison of a Second-Order versus a Fourth- Order Lapacian Operator in the Mutigrid Agorithm Kaushik Datta (kdatta@cs.berkeey.edu Math Project May 9, 003 Abstract In this paper, the mutigrid agorithm

More information

Endoscopic Motion Compensation of High Speed Videoendoscopy

Endoscopic Motion Compensation of High Speed Videoendoscopy Endoscopic Motion Compensation of High Speed Videoendoscopy Bharath avuri Department of Computer Science and Engineering, University of South Caroina, Coumbia, SC - 901. ravuri@cse.sc.edu Abstract. High

More information

WATERMARKING GIS DATA FOR DIGITAL MAP COPYRIGHT PROTECTION

WATERMARKING GIS DATA FOR DIGITAL MAP COPYRIGHT PROTECTION WATERMARKING GIS DATA FOR DIGITAL MAP COPYRIGHT PROTECTION Shen Tao Chinese Academy of Surveying and Mapping, Beijing 100039, China shentao@casm.ac.cn Xu Dehe Institute of resources and environment, North

More information

Image Segmentation Using Semi-Supervised k-means

Image Segmentation Using Semi-Supervised k-means I J C T A, 9(34) 2016, pp. 595-601 Internationa Science Press Image Segmentation Using Semi-Supervised k-means Reza Monsefi * and Saeed Zahedi * ABSTRACT Extracting the region of interest is a very chaenging

More information

Silhouette Partitioning for Height Field Ray Tracing

Silhouette Partitioning for Height Field Ray Tracing Sihouette Partitioning for Height Fied Ray Tracing Tomas Sakaauskas Vinius University Naugarduko 24, Lithuania,03225,Vinius tomas.sakaauskas@prewise.t ABSTRACT This paper presents parae agorithm to ray

More information

On Upper Bounds for Assortment Optimization under the Mixture of Multinomial Logit Models

On Upper Bounds for Assortment Optimization under the Mixture of Multinomial Logit Models On Upper Bounds for Assortment Optimization under the Mixture of Mutinomia Logit Modes Sumit Kunnumka September 30, 2014 Abstract The assortment optimization probem under the mixture of mutinomia ogit

More information

Substitute Model of Deep-groove Ball Bearings in Numeric Analysis of Complex Constructions Like Manipulators

Substitute Model of Deep-groove Ball Bearings in Numeric Analysis of Complex Constructions Like Manipulators Mechanics and Mechanica Engineering Vo. 12, No. 4 (2008) 349 356 c Technica University of Lodz Substitute Mode of Deep-groove Ba Bearings in Numeric Anaysis of Compex Constructions Like Manipuators Leszek

More information

Adaptive 360 VR Video Streaming: Divide and Conquer!

Adaptive 360 VR Video Streaming: Divide and Conquer! Adaptive 360 VR Video Streaming: Divide and Conquer! Mohammad Hosseini *, Viswanathan Swaminathan * University of Iinois at Urbana-Champaign (UIUC) Adobe Research, San Jose, USA Emai: shossen2@iinois.edu,

More information

Discrete elastica model for shape design of grid shells

Discrete elastica model for shape design of grid shells Abstracts for IASS Annua Symposium 017 5 8th September, 017, Hamburg, Germany Annette Böge, Manfred Grohmann (eds.) Discrete eastica mode for shape design of grid shes Yusuke SAKAI* and Makoto OHSAKI a

More information

Proceedings of the International Conference on Systolic Arrays, San Diego, California, U.S.A., May 25-27, 1988 AN EFFICIENT ASYNCHRONOUS MULTIPLIER!

Proceedings of the International Conference on Systolic Arrays, San Diego, California, U.S.A., May 25-27, 1988 AN EFFICIENT ASYNCHRONOUS MULTIPLIER! [1,2] have, in theory, revoutionized cryptography. Unfortunatey, athough offer many advantages over conventiona and authentication), such cock synchronization in this appication due to the arge operand

More information

Outline. Parallel Numerical Algorithms. Forward Substitution. Triangular Matrices. Solving Triangular Systems. Back Substitution. Parallel Algorithm

Outline. Parallel Numerical Algorithms. Forward Substitution. Triangular Matrices. Solving Triangular Systems. Back Substitution. Parallel Algorithm Outine Parae Numerica Agorithms Chapter 8 Prof. Michae T. Heath Department of Computer Science University of Iinois at Urbana-Champaign CS 554 / CSE 512 1 2 3 4 Trianguar Matrices Michae T. Heath Parae

More information

A NOVEL GENERAL FORMULATION FOR SINGULAR STRESS FIELD USING THE ES-FEM METHOD FOR THE ANALYSIS OF MIXED-MODE CRACKS

A NOVEL GENERAL FORMULATION FOR SINGULAR STRESS FIELD USING THE ES-FEM METHOD FOR THE ANALYSIS OF MIXED-MODE CRACKS Internationa Journa of Computationa Methods Vo. 7, No. 1 2010 191 214 c Word Scientific Pubishing Company DOI: 10.1142/S0219876210002131 A NOVEL GENERAL FORMULATION FOR SINGULAR STRESS FIELD USING THE

More information

MULTIGRID REDUCTION IN TIME FOR NONLINEAR PARABOLIC PROBLEMS: A CASE STUDY

MULTIGRID REDUCTION IN TIME FOR NONLINEAR PARABOLIC PROBLEMS: A CASE STUDY MULTIGRID REDUCTION IN TIME FOR NONLINEAR PARABOLIC PROBLEMS: A CASE STUDY R.D. FALGOUT, T.A. MANTEUFFEL, B. O NEILL, AND J.B. SCHRODER Abstract. The need for paraeism in the time dimension is being driven

More information

Quality Assessment using Tone Mapping Algorithm

Quality Assessment using Tone Mapping Algorithm Quaity Assessment using Tone Mapping Agorithm Nandiki.pushpa atha, Kuriti.Rajendra Prasad Research Schoar, Assistant Professor, Vignan s institute of engineering for women, Visakhapatnam, Andhra Pradesh,

More information

Online Learning for Hierarchical Networks of Locally Arranged Models using a Support Vector Domain Model

Online Learning for Hierarchical Networks of Locally Arranged Models using a Support Vector Domain Model Proceedings of Internationa Joint Conference on Neura Networks, Orando, Forida, USA, August 12-17, 2007 Onine Learning for Hierarchica Networks of Locay Arranged Modes using a Support Vector Domain Mode

More information

Research on UAV Fixed Area Inspection based on Image Reconstruction

Research on UAV Fixed Area Inspection based on Image Reconstruction Research on UAV Fixed Area Inspection based on Image Reconstruction Kun Cao a, Fei Wu b Schoo of Eectronic and Eectrica Engineering, Shanghai University of Engineering Science, Abstract Shanghai 20600,

More information

A Design Method for Optimal Truss Structures with Certain Redundancy Based on Combinatorial Rigidity Theory

A Design Method for Optimal Truss Structures with Certain Redundancy Based on Combinatorial Rigidity Theory 0 th Word Congress on Structura and Mutidiscipinary Optimization May 9 -, 03, Orando, Forida, USA A Design Method for Optima Truss Structures with Certain Redundancy Based on Combinatoria Rigidity Theory

More information

Absolute three-dimensional shape measurement with two-frequency square binary patterns

Absolute three-dimensional shape measurement with two-frequency square binary patterns 871 Vo. 56, No. 31 / November 1 217 / Appied Optics Research Artice Absoute three-dimensiona shape measurement with two-frequency square binary patterns CHUFAN JIANG AND SONG ZHANG* Schoo of Mechanica

More information

CLOUD RADIO ACCESS NETWORK WITH OPTIMIZED BASE-STATION CACHING

CLOUD RADIO ACCESS NETWORK WITH OPTIMIZED BASE-STATION CACHING CLOUD RADIO ACCESS NETWORK WITH OPTIMIZED BASE-STATION CACHING Binbin Dai and Wei Yu Ya-Feng Liu Department of Eectrica and Computer Engineering University of Toronto, Toronto ON, Canada M5S 3G4 Emais:

More information

Large-Scale Modeling of Parametric Surfaces using Spherical Harmonics

Large-Scale Modeling of Parametric Surfaces using Spherical Harmonics Large-Scae Modeing of Parametric Surfaces using Spherica Harmonics Li Shen Dept of Computer and Info Science University of Massachusetts Dartmouth N Dartmouth, MA 2747 shen@umassdedu Moo K Chung Department

More information

Language Identification for Texts Written in Transliteration

Language Identification for Texts Written in Transliteration Language Identification for Texts Written in Transiteration Andrey Chepovskiy, Sergey Gusev, Margarita Kurbatova Higher Schoo of Economics, Data Anaysis and Artificia Inteigence Department, Pokrovskiy

More information

As Michi Henning and Steve Vinoski showed 1, calling a remote

As Michi Henning and Steve Vinoski showed 1, calling a remote Reducing CORBA Ca Latency by Caching and Prefetching Bernd Brügge and Christoph Vismeier Technische Universität München Method ca atency is a major probem in approaches based on object-oriented middeware

More information

JOINT IMAGE REGISTRATION AND EXAMPLE-BASED SUPER-RESOLUTION ALGORITHM

JOINT IMAGE REGISTRATION AND EXAMPLE-BASED SUPER-RESOLUTION ALGORITHM JOINT IMAGE REGISTRATION AND AMPLE-BASED SUPER-RESOLUTION ALGORITHM Hyo-Song Kim, Jeyong Shin, and Rae-Hong Park Department of Eectronic Engineering, Schoo of Engineering, Sogang University 35 Baekbeom-ro,

More information

Replication of Virtual Network Functions: Optimizing Link Utilization and Resource Costs

Replication of Virtual Network Functions: Optimizing Link Utilization and Resource Costs Repication of Virtua Network Functions: Optimizing Link Utiization and Resource Costs Francisco Carpio, Wogang Bziuk and Admea Jukan Technische Universität Braunschweig, Germany Emai:{f.carpio, w.bziuk,

More information

Multiple Plane Phase Retrieval Based On Inverse Regularized Imaging and Discrete Diffraction Transform

Multiple Plane Phase Retrieval Based On Inverse Regularized Imaging and Discrete Diffraction Transform Mutipe Pane Phase Retrieva Based On Inverse Reguaried Imaging and Discrete Diffraction Transform Artem Migukin, Vadimir Katkovnik, and Jaakko Astoa Department of Signa Processing, Tampere University of

More information

Real-time per-pixel rendering of textiles for virtual textile catalogues

Real-time per-pixel rendering of textiles for virtual textile catalogues Rea-time per-pixe rendering of texties for virtua textie cataogues Andy Spence, Mike Robb, Mark Timmins 2 & Mike Chanter Schoo of Mathematica & Computer Sciences, Heriot-Watt University, Edinburgh, EH4

More information

Revisions for VISRAD

Revisions for VISRAD Revisions for VISRAD 16.0.0 Support has been added for the SLAC MEC target chamber: 4 beams have been added to the Laser System: X-ray beam (fixed in Port P 90-180), 2 movabe Nd:Gass (ong-puse) beams,

More information

Solving Large Double Digestion Problems for DNA Restriction Mapping by Using Branch-and-Bound Integer Linear Programming

Solving Large Double Digestion Problems for DNA Restriction Mapping by Using Branch-and-Bound Integer Linear Programming The First Internationa Symposium on Optimization and Systems Bioogy (OSB 07) Beijing, China, August 8 10, 2007 Copyright 2007 ORSC & APORC pp. 267 279 Soving Large Doube Digestion Probems for DNA Restriction

More information

Intro to Programming & C Why Program? 1.2 Computer Systems: Hardware and Software. Why Learn to Program?

Intro to Programming & C Why Program? 1.2 Computer Systems: Hardware and Software. Why Learn to Program? Intro to Programming & C++ Unit 1 Sections 1.1-3 and 2.1-10, 2.12-13, 2.15-17 CS 1428 Spring 2018 Ji Seaman 1.1 Why Program? Computer programmabe machine designed to foow instructions Program a set of

More information

Further Concepts in Geometry

Further Concepts in Geometry ppendix F Further oncepts in Geometry F. Exporing ongruence and Simiarity Identifying ongruent Figures Identifying Simiar Figures Reading and Using Definitions ongruent Trianges assifying Trianges Identifying

More information

GPU Implementation of Parallel SVM as Applied to Intrusion Detection System

GPU Implementation of Parallel SVM as Applied to Intrusion Detection System GPU Impementation of Parae SVM as Appied to Intrusion Detection System Sudarshan Hiray Research Schoar, Department of Computer Engineering, Vishwakarma Institute of Technoogy, Pune, India sdhiray7@gmai.com

More information

Reference trajectory tracking for a multi-dof robot arm

Reference trajectory tracking for a multi-dof robot arm Archives of Contro Sciences Voume 5LXI, 5 No. 4, pages 53 57 Reference trajectory tracking for a muti-dof robot arm RÓBERT KRASŇANSKÝ, PETER VALACH, DÁVID SOÓS, JAVAD ZARBAKHSH This paper presents the

More information

FIRST BEZIER POINT (SS) R LE LE. φ LE FIRST BEZIER POINT (PS)

FIRST BEZIER POINT (SS) R LE LE. φ LE FIRST BEZIER POINT (PS) Singe- and Muti-Objective Airfoi Design Using Genetic Agorithms and Articia Inteigence A.P. Giotis K.C. Giannakogou y Nationa Technica University of Athens, Greece Abstract Transonic airfoi design probems

More information

Arithmetic Coding. Prof. Ja-Ling Wu. Department of Computer Science and Information Engineering National Taiwan University

Arithmetic Coding. Prof. Ja-Ling Wu. Department of Computer Science and Information Engineering National Taiwan University Arithmetic Coding Prof. Ja-Ling Wu Department of Computer Science and Information Engineering Nationa Taiwan University F(X) Shannon-Fano-Eias Coding W..o.g. we can take X={,,,m}. Assume p()>0 for a. The

More information

Distance Weighted Discrimination and Second Order Cone Programming

Distance Weighted Discrimination and Second Order Cone Programming Distance Weighted Discrimination and Second Order Cone Programming Hanwen Huang, Xiaosun Lu, Yufeng Liu, J. S. Marron, Perry Haaand Apri 3, 2012 1 Introduction This vignette demonstrates the utiity and

More information

Real-Time Feature Descriptor Matching via a Multi-Resolution Exhaustive Search Method

Real-Time Feature Descriptor Matching via a Multi-Resolution Exhaustive Search Method 297 Rea-Time Feature escriptor Matching via a Muti-Resoution Ehaustive Search Method Chi-Yi Tsai, An-Hung Tsao, and Chuan-Wei Wang epartment of Eectrica Engineering, Tamang University, New Taipei City,

More information

Digital Image Watermarking Algorithm Based on Fast Curvelet Transform

Digital Image Watermarking Algorithm Based on Fast Curvelet Transform J. Software Engineering & Appications, 010, 3, 939-943 doi:10.436/jsea.010.310111 Pubished Onine October 010 (http://www.scirp.org/journa/jsea) 939 igita Image Watermarking Agorithm Based on Fast Curveet

More information

An Edge Guided Image Interpolation Algorithm via Directional Filtering and Data Fusion

An Edge Guided Image Interpolation Algorithm via Directional Filtering and Data Fusion An Edge Guided Image Interpoation Agoritm via Directiona Fitering and Data Fusion Lei Zang *a, Member, IEEE, and Xiaoin Wu b, Senior Member, IEEE a Dept. of Computing, Te Hong Kong Poytecnic University

More information

Performance Enhancement of 2D Face Recognition via Mosaicing

Performance Enhancement of 2D Face Recognition via Mosaicing Performance Enhancement of D Face Recognition via Mosaicing Richa Singh, Mayank Vatsa, Arun Ross, Afze Noore West Virginia University, Morgantown, WV 6506 {richas, mayankv, ross, noore}@csee.wvu.edu Abstract

More information

H 10 M645 GETTING STA RT E D. Phase One A/S Roskildevej 39 DK-2000 Frederiksberg Denmark Tel Fax

H 10 M645 GETTING STA RT E D. Phase One A/S Roskildevej 39 DK-2000 Frederiksberg Denmark Tel Fax H 10 M645 GETTING STA RT E D Phase One A/S Roskidevej 39 DK-2000 Frederiksberg Denmark Te +45 36 46 01 11 Fax +45 36 46 02 22 Phase One U.S. 24 Woodbine Ave Northport, New York 11768 USA Te +00 631-757-0400

More information

Improving image quality in low snr parallel acquisition using a weighted least squares GRAPPA reconstruction

Improving image quality in low snr parallel acquisition using a weighted least squares GRAPPA reconstruction RESEARCH Improving image quait in ow snr parae acquisition using a weighted east squares GRAPPA reconstruction We anaze the performance of a Weighted Least Squares (W) GRAPPA caibration for improving the

More information

Response Surface Model Updating for Nonlinear Structures

Response Surface Model Updating for Nonlinear Structures Response Surface Mode Updating for Noninear Structures Gonaz Shahidi a, Shamim Pakzad b a PhD Student, Department of Civi and Environmenta Engineering, Lehigh University, ATLSS Engineering Research Center,

More information

A Memory Grouping Method for Sharing Memory BIST Logic

A Memory Grouping Method for Sharing Memory BIST Logic A Memory Grouping Method for Sharing Memory BIST Logic Masahide Miyazai, Tomoazu Yoneda, and Hideo Fuiwara Graduate Schoo of Information Science, Nara Institute of Science and Technoogy (NAIST), 8916-5

More information

Fuzzy Controller for a Dynamic Window in Elliptic Curve Cryptography Wireless Networks for Scalar Multiplication

Fuzzy Controller for a Dynamic Window in Elliptic Curve Cryptography Wireless Networks for Scalar Multiplication 6th Asia-Pacific Conference on Communications Fuzzy Controer for a Dynamic Window in Eiptic Curve Cryptography Wireess Networks for Scaar Mutipication Xu Huang Facuty of Information Sciences and Engineering

More information

Numerical Simulation of 3D Bubbles Rising in Viscous Liquids using a Front Tracking Method

Numerical Simulation of 3D Bubbles Rising in Viscous Liquids using a Front Tracking Method Numerica Simuation of 3D Bubbes Rising in Viscous Liquids using a Front Tracking Method Jinsong Hua a, Jan F. Stene b and Ping Lin b a Institute of High Performance Computing, 1 Science Park Road, #01-01

More information

Joint disparity and motion eld estimation in. stereoscopic image sequences. Ioannis Patras, Nikos Alvertos and Georgios Tziritas y.

Joint disparity and motion eld estimation in. stereoscopic image sequences. Ioannis Patras, Nikos Alvertos and Georgios Tziritas y. FORTH-ICS / TR-157 December 1995 Joint disparity and motion ed estimation in stereoscopic image sequences Ioannis Patras, Nikos Avertos and Georgios Tziritas y Abstract This work aims at determining four

More information

Published in: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, April, 2003

Published in: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, April, 2003 Aaborg Universitet Compressed Domain Packet Loss Conceament of Sinusoiday Coded Speech Rødbro, Christoffer Asgaard; Christensen, Mads Græsbø; Andersen, Søren Vang; Jensen, Søren Hodt Pubished in: Proc.

More information

Neural Network Enhancement of the Los Alamos Force Deployment Estimator

Neural Network Enhancement of the Los Alamos Force Deployment Estimator Missouri University of Science and Technoogy Schoars' Mine Eectrica and Computer Engineering Facuty Research & Creative Works Eectrica and Computer Engineering 1-1-1994 Neura Network Enhancement of the

More information

Relocation of Hopping Sensors

Relocation of Hopping Sensors 28 IEEE Internationa Conference on Robotics and Automation Pasadena, CA, USA, May 9-23, 28 Reocation of Hopping Sensors Zhiwei Cen Googe Inc. 6 Amphitheatre Pky Mountain View, CA 9443, USA Matt W. Mutka

More information

Background Oriented Schlieren technique sensitivity, accuracy, resolution and application to a three-dimensional density field

Background Oriented Schlieren technique sensitivity, accuracy, resolution and application to a three-dimensional density field Background Oriented Schieren technique sensitivity, accuracy, resoution and appication to a three-dimensiona density fied Erik Godhahn 1, Jörg Seume 2 1: Institute of Turbomachinery and Fuid-Dynamics,

More information

Quaternion Support Vector Classifier

Quaternion Support Vector Classifier Quaternion Support Vector Cassifier G. López-Gonzáez, Nancy Arana-Danie, and Eduardo Bayro-Corrochano CINVESTAV - Unidad Guadaajara, Av. de Bosque 1145, Coonia e Bajo, Zapopan, Jaisco, México {geopez,edb}@gd.cinvestav.mx

More information

Image Processing Technology of FLIR-based Enhanced Vision System

Image Processing Technology of FLIR-based Enhanced Vision System 25 TH INTERNATIONAL CONGRESS OF THE AERONAUTICAL SCIENCES Image Processing Technoogy of FLIR-based Enhanced Vision System Ding Quan Xin, Zhu Rong Gang,Zhao Zhen Yu Luoyang Institute of Eectro-optica Equipment

More information

An Exponential Time 2-Approximation Algorithm for Bandwidth

An Exponential Time 2-Approximation Algorithm for Bandwidth An Exponentia Time 2-Approximation Agorithm for Bandwidth Martin Fürer 1, Serge Gaspers 2, Shiva Prasad Kasiviswanathan 3 1 Computer Science and Engineering, Pennsyvania State University, furer@cse.psu.edu

More information

Elements of Computer Vision: Multiple View Geometry. 1 Introduction. 2 Elements of Geometry. Andrea Fusiello

Elements of Computer Vision: Multiple View Geometry. 1 Introduction. 2 Elements of Geometry. Andrea Fusiello Eements of Computer Vision: Mutipe View Geometry. Andrea Fusieo http://www.sci.univr.it/~fusieo June 20, 2005 Fig. 1. Exampe of reconstruction from the five images shown in the top row. 3 1 Introduction

More information

A Petrel Plugin for Surface Modeling

A Petrel Plugin for Surface Modeling A Petre Pugin for Surface Modeing R. M. Hassanpour, S. H. Derakhshan and C. V. Deutsch Structure and thickness uncertainty are important components of any uncertainty study. The exact ocations of the geoogica

More information

tread base carc1 carc2 sidewall2 beadflat beadcushion treadfine basefine Y X Z

tread base carc1 carc2 sidewall2 beadflat beadcushion treadfine basefine Y X Z APPLICATION OF THE FINITE ELEMENT METHOD TO THE ANALYSIS OF AUTOMOBILE TIRES H.-J. PAYER, G. MESCHKE AND H.A. MANG Institute for Strength of Materias Vienna University of Technoogy Karspatz 13/E202, A-1040

More information

5940 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 13, NO. 11, NOVEMBER 2014

5940 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 13, NO. 11, NOVEMBER 2014 5940 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 13, NO. 11, NOVEMBER 014 Topoogy-Transparent Scheduing in Mobie Ad Hoc Networks With Mutipe Packet Reception Capabiity Yiming Liu, Member, IEEE,

More information

Chapter 3 ATI. Jason L. Mitchell

Chapter 3 ATI. Jason L. Mitchell Chapter 3 ATI Jason L. Mitchell SIGGRAPH 2002 - State of the Art in Hardware Shading Course Pixel Shading with DirectX 8.1 and the ATI RADEON 8500 Jason L. Mitchell JasonM@ati.com 3D Application Research

More information

Optimized Base-Station Cache Allocation for Cloud Radio Access Network with Multicast Backhaul

Optimized Base-Station Cache Allocation for Cloud Radio Access Network with Multicast Backhaul Optimized Base-Station Cache Aocation for Coud Radio Access Network with Muticast Backhau Binbin Dai, Student Member, IEEE, Ya-Feng Liu, Member, IEEE, and Wei Yu, Feow, IEEE arxiv:804.0730v [cs.it] 28

More information

FREE-FORM ANISOTROPY: A NEW METHOD FOR CRACK DETECTION ON PAVEMENT SURFACE IMAGES

FREE-FORM ANISOTROPY: A NEW METHOD FOR CRACK DETECTION ON PAVEMENT SURFACE IMAGES FREE-FORM ANISOTROPY: A NEW METHOD FOR CRACK DETECTION ON PAVEMENT SURFACE IMAGES Tien Sy Nguyen, Stéphane Begot, Forent Ducuty, Manue Avia To cite this version: Tien Sy Nguyen, Stéphane Begot, Forent

More information

Fast Methods for Kernel-based Text Analysis

Fast Methods for Kernel-based Text Analysis Proceedings of the 41st Annua Meeting of the Association for Computationa Linguistics, Juy 2003, pp. 24-31. Fast Methods for Kerne-based Text Anaysis Taku Kudo and Yuji Matsumoto Graduate Schoo of Information

More information

Unconstrained Automatic Image Matching Using Multiresolutional Critical-Point Filters

Unconstrained Automatic Image Matching Using Multiresolutional Critical-Point Filters 994 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL., NO. 9, SEPTEMBER 998 Unconstrained Automatic Image Matching Using Mutiresoutiona Critica-Point Fiters Yoshihisa Shinagawa, Member,

More information

Mobile App Recommendation: Maximize the Total App Downloads

Mobile App Recommendation: Maximize the Total App Downloads Mobie App Recommendation: Maximize the Tota App Downoads Zhuohua Chen Schoo of Economics and Management Tsinghua University chenzhh3.12@sem.tsinghua.edu.cn Yinghui (Catherine) Yang Graduate Schoo of Management

More information

A Novel Linear-Polynomial Kernel to Construct Support Vector Machines for Speech Recognition

A Novel Linear-Polynomial Kernel to Construct Support Vector Machines for Speech Recognition Journa of Computer Science 7 (7): 99-996, 20 ISSN 549-3636 20 Science Pubications A Nove Linear-Poynomia Kerne to Construct Support Vector Machines for Speech Recognition Bawant A. Sonkambe and 2 D.D.

More information

A Novel Method for Early Software Quality Prediction Based on Support Vector Machine

A Novel Method for Early Software Quality Prediction Based on Support Vector Machine A Nove Method for Eary Software Quaity Prediction Based on Support Vector Machine Fei Xing 1,PingGuo 1;2, and Michae R. Lyu 2 1 Department of Computer Science Beijing Norma University, Beijing, 1875, China

More information

CERIAS Tech Report Replicated Parallel I/O without Additional Scheduling Costs by Mikhail J. Atallah Center for Education and Research

CERIAS Tech Report Replicated Parallel I/O without Additional Scheduling Costs by Mikhail J. Atallah Center for Education and Research CERIAS Tech Report 2003-50 Repicated Parae I/O without Additiona Scheduing Costs by Mikhai J. Ataah Center for Education and Research Information Assurance and Security Purdue University, West Lafayette,

More information

Collinearity and Coplanarity Constraints for Structure from Motion

Collinearity and Coplanarity Constraints for Structure from Motion Coinearity and Copanarity Constraints for Structure from Motion Gang Liu 1, Reinhard Kette 2, and Bodo Rosenhahn 3 1 Institute of Information Sciences and Technoogy, Massey University, New Zeaand, Department

More information

Research on the overall optimization method of well pattern in water drive reservoirs

Research on the overall optimization method of well pattern in water drive reservoirs J Petro Expor Prod Techno (27) 7:465 47 DOI.7/s322-6-265-3 ORIGINAL PAPER - EXPLORATION ENGINEERING Research on the overa optimization method of we pattern in water drive reservoirs Zhibin Zhou Jiexiang

More information

Filtering. Yao Wang Polytechnic University, Brooklyn, NY 11201

Filtering. Yao Wang Polytechnic University, Brooklyn, NY 11201 Spatia Domain Linear Fitering Yao Wang Poytechnic University Brookyn NY With contribution rom Zhu Liu Onur Gueryuz and Gonzaez/Woods Digita Image Processing ed Introduction Outine Noise remova using ow-pass

More information

Self-Control Cyclic Access with Time Division - A MAC Proposal for The HFC System

Self-Control Cyclic Access with Time Division - A MAC Proposal for The HFC System Sef-Contro Cycic Access with Time Division - A MAC Proposa for The HFC System S.M. Jiang, Danny H.K. Tsang, Samue T. Chanson Hong Kong University of Science & Technoogy Cear Water Bay, Kowoon, Hong Kong

More information

Application of Intelligence Based Genetic Algorithm for Job Sequencing Problem on Parallel Mixed-Model Assembly Line

Application of Intelligence Based Genetic Algorithm for Job Sequencing Problem on Parallel Mixed-Model Assembly Line American J. of Engineering and Appied Sciences 3 (): 5-24, 200 ISSN 94-7020 200 Science Pubications Appication of Inteigence Based Genetic Agorithm for Job Sequencing Probem on Parae Mixed-Mode Assemby

More information

ACTIVE LEARNING ON WEIGHTED GRAPHS USING ADAPTIVE AND NON-ADAPTIVE APPROACHES. Eyal En Gad, Akshay Gadde, A. Salman Avestimehr and Antonio Ortega

ACTIVE LEARNING ON WEIGHTED GRAPHS USING ADAPTIVE AND NON-ADAPTIVE APPROACHES. Eyal En Gad, Akshay Gadde, A. Salman Avestimehr and Antonio Ortega ACTIVE LEARNING ON WEIGHTED GRAPHS USING ADAPTIVE AND NON-ADAPTIVE APPROACHES Eya En Gad, Akshay Gadde, A. Saman Avestimehr and Antonio Ortega Department of Eectrica Engineering University of Southern

More information

Crossing Minimization Problems of Drawing Bipartite Graphs in Two Clusters

Crossing Minimization Problems of Drawing Bipartite Graphs in Two Clusters Crossing Minimiation Probems o Drawing Bipartite Graphs in Two Custers Lanbo Zheng, Le Song, and Peter Eades Nationa ICT Austraia, and Schoo o Inormation Technoogies, University o Sydney,Austraia Emai:

More information

Providing Hop-by-Hop Authentication and Source Privacy in Wireless Sensor Networks

Providing Hop-by-Hop Authentication and Source Privacy in Wireless Sensor Networks The 31st Annua IEEE Internationa Conference on Computer Communications: Mini-Conference Providing Hop-by-Hop Authentication and Source Privacy in Wireess Sensor Networks Yun Li Jian Li Jian Ren Department

More information

Relative Positioning from Model Indexing

Relative Positioning from Model Indexing Reative Positioning from Mode Indexing Stefan Carsson Computationa Vision and Active Perception Laboratory (CVAP)* Roya Institute of Technoogy (KTH), Stockhom, Sweden Abstract We show how to determine

More information

An Introduction to Design Patterns

An Introduction to Design Patterns An Introduction to Design Patterns 1 Definitions A pattern is a recurring soution to a standard probem, in a context. Christopher Aexander, a professor of architecture Why woud what a prof of architecture

More information

Analytic Spherical Harmonic Coefficients for Polygonal Area Lights

Analytic Spherical Harmonic Coefficients for Polygonal Area Lights Anaytic Spherica Harmonic Coefficients for Poygona Area Lights JINGWEN WANG, University of Caifornia, San Diego RAVI RAMAMOORTHI, University of Caifornia, San Diego Spherica Harmonic (SH) ighting is widey

More information

PICO: PARAMETERS FOR THE IMPATIENT COSMOLOGIST

PICO: PARAMETERS FOR THE IMPATIENT COSMOLOGIST The Astrophysica Journa, 654:2Y11, 2007 January 1 # 2007. The American Astronomica Society. A rights reserved. Printed in U.S.A. A PICO: PARAMETERS FOR THE IMPATIENT COSMOLOGIST Wiiam A. Fendt 1 and Benjamin

More information

Grating cell operator features for oriented texture segmentation

Grating cell operator features for oriented texture segmentation Appeared in in: Proc. of the 14th Int. Conf. on Pattern Recognition, Brisbane, Austraia, August 16-20, 1998, pp.1010-1014. Grating ce operator features for oriented texture segmentation P. Kruizinga and

More information