Mid-term review ECE 161C Electrical and Computer Engineering University of California San Diego

Size: px
Start display at page:

Download "Mid-term review ECE 161C Electrical and Computer Engineering University of California San Diego"

Transcription

1 Mid-term review ECE 161C Electrical and Computer Engineering Univerity of California San Diego Nuno Vaconcelo Spring We have een in cla that one popular technique for edge detection i the Canny edge detector. It contain three parameter: a moothing parameter σ, and two threhold t 1 and t 2 that implement an hyterei mechanim which allow control over the likelihood of tarting v following a contour. Here we will jut worry with the threhold that i ued to tart a contour, the other one will remain contant. We denote the threhold that we allow to change by t. Figure 1 and 2 preent an image and three edge map obtained with different parameter etting. The combination of parameter that we ued to obtain the edge map are given by the following table. Eperiment t σ For each eperiment, indicate which i the reulting edge map. Provide an eplanation for your aignment, i.e. why did you aign edge map to eperiment y? (Note: the aignment themelve are only worth 10% of the grade in thi problem - make ure you provide a clear eplanation of your thought proce in determining them). 2. Conider the equence (n 1,n 2 ) whoe dicrete pace Fourier tranform i X(ω 1,ω 2 )=2+2co(w 1 ) 2co(w 2 ) a) Determine (n 1,n 2 ). b) I [n 1,n 2 ] a eparable equence? Suppoe that we can add or ubtract non-zero value to the (n 1,n 2 ) for which [n 1,n 2 ] = 0. What i the minimum number of entrie that need to be made nonzero in order to change the eparability of the equence (i.e. make it non-eparable if it i eparable or vice-vera)? Eplain why. c) Suppoe that we can make the non-zero value of [n 1,n 2 ] equal to zero. What i the minimum number of entrie that need to be made zero in order to change the eparability of the equence (i.e. make it non-eparable if it i eparable or vice-vera)?. Eplain why. 1

2 a) Image b) Edge map 1 Figure 1: 2

3 c) Edge map d) Edge map 3 Figure 2: 3

4 y y r P 1 r P 1 z z a) 2 + y 2 + z 2 = r 2 b) 2 + y 2 = r 2 y P 1 y z O 1 2 a b c 3 c) 2 + z 2 = y d) θ 1 =45,θ 2 =30,θ 3 =60 Figure 3: Lambertian urface with uniform albedo. 3. Figure 3, a) through d), how four Lambertian urface with uniform albedo. Each of thee urface i illuminated by a point ource at infinity (E = 1), the direction of which i indicated by the vector. The radiance reflected from the point P 0 on each urface i 10 unit. Determine the albedo of the urface and derive an epreion for the radiance reflected from a general point P 1 =(, y, z). Comment on the reulting illumination pattern for each cae. 4

5 4. Conider the problem of correcting a poorly hot photograph, uch a that hown in the left ide of figure 5. The problem i that the camera wa not properly oriented, and image feature do not appear in their natural orientation, e.g. the building do not appear to be vertical. We would like to correct the image, in order to obtain omething like the one hown on the right ide of the figure. We model the problem a hown below: the camera that took the picture wa ubject to a rotation (with repect to the ideally aligned camera ) of angle β around the optical ai. We let i, j, k be the coordinate ytem aociated with the ideal camera and i, j, k the one aociated with the real camera. Image plane j k i j (X,Y,Z) i k=k j 3D cene i Figure 4: Left: imaging et-up for problem 4. Right: the coordinate ytem of the real camera (i, j, k ), i a rotation of the coordinate ytem of the ideal camera (i, j, k). a) Show that the coordinate ytem are related by i = co(β) i in(β) j j = in(β) i +co(β) j k = k b) Conider a point of coordinate (X, Y, Z) in the old coordinate ytem. Uing a), write down the coordinate (X,Y,Z ) of the point in the new coordinate ytem a a function of (X, Y, Z). (Note: if you find yourelf inverting the ytem of equation in a) you are probably going in the wrong direction.) c) Let (, y) be the image coordinate of the perpective projection of the point (X, Y, Z) fortheold camera, and (,y ) the image coordinate of the perpective projection of (X,Y,Z ) under the new one. Derive the equation that determine (,y ) a a function of (, y). d) Uing the equation derived in c) it i poible to determine the impact of the tranformation on the ditance between any two image point. Conider two point a =( 1,y 1 )andb =( 2,y 2 ), and the point a and b into which they are mapped. What i the relationhip between a b 2 and a b 2? (Note: here we are talking about the Euclidean ditance, i.e. for a =(, y) a 2 = a T a = 2 + y 2.) 5

6 Figure 5: Left: poorly hot photograph. Right: deired image. 6

Motion Control (wheeled robots)

Motion Control (wheeled robots) 3 Motion Control (wheeled robot) Requirement for Motion Control Kinematic / dynamic model of the robot Model of the interaction between the wheel and the ground Definition of required motion -> peed control,

More information

Universität Augsburg. Institut für Informatik. Approximating Optimal Visual Sensor Placement. E. Hörster, R. Lienhart.

Universität Augsburg. Institut für Informatik. Approximating Optimal Visual Sensor Placement. E. Hörster, R. Lienhart. Univerität Augburg à ÊÇÅÍÆ ËÀǼ Approximating Optimal Viual Senor Placement E. Hörter, R. Lienhart Report 2006-01 Januar 2006 Intitut für Informatik D-86135 Augburg Copyright c E. Hörter, R. Lienhart Intitut

More information

CS201: Data Structures and Algorithms. Assignment 2. Version 1d

CS201: Data Structures and Algorithms. Assignment 2. Version 1d CS201: Data Structure and Algorithm Aignment 2 Introduction Verion 1d You will compare the performance of green binary earch tree veru red-black tree by reading in a corpu of text, toring the word and

More information

Drawing Lines in 2 Dimensions

Drawing Lines in 2 Dimensions Drawing Line in 2 Dimenion Drawing a traight line (or an arc) between two end point when one i limited to dicrete pixel require a bit of thought. Conider the following line uperimpoed on a 2 dimenional

More information

Course Updates. Reminders: 1) Assignment #13 due Monday. 2) Mirrors & Lenses. 3) Review for Final: Wednesday, May 5th

Course Updates. Reminders: 1) Assignment #13 due Monday. 2) Mirrors & Lenses. 3) Review for Final: Wednesday, May 5th Coure Update http://www.phy.hawaii.edu/~varner/phys272-spr0/phyic272.html Reminder: ) Aignment #3 due Monday 2) Mirror & Lene 3) Review for Final: Wedneday, May 5th h R- R θ θ -R h Spherical Mirror Infinite

More information

Optimizing Synchronous Systems for Multi-Dimensional. Notre Dame, IN Ames, Iowa computation is an optimization problem (b) circuit

Optimizing Synchronous Systems for Multi-Dimensional. Notre Dame, IN Ames, Iowa computation is an optimization problem (b) circuit Optimizing Synchronou Sytem for ulti-imenional pplication Nelon L. Pao and Edwin H.-. Sha Liang-Fang hao ept. of omputer Science & Eng. ept. of Electrical & omputer Eng. Univerity of Notre ame Iowa State

More information

An Intro to LP and the Simplex Algorithm. Primal Simplex

An Intro to LP and the Simplex Algorithm. Primal Simplex An Intro to LP and the Simplex Algorithm Primal Simplex Linear programming i contrained minimization of a linear objective over a olution pace defined by linear contraint: min cx Ax b l x u A i an m n

More information

REVERSE KINEMATIC ANALYSIS OF THE SPATIAL SIX AXIS ROBOTIC MANIPULATOR WITH CONSECUTIVE JOINT AXES PARALLEL

REVERSE KINEMATIC ANALYSIS OF THE SPATIAL SIX AXIS ROBOTIC MANIPULATOR WITH CONSECUTIVE JOINT AXES PARALLEL Proceeding of the ASME 007 International Deign Engineering Technical Conference & Computer and Information in Engineering Conference IDETC/CIE 007 September 4-7, 007 La Vega, Nevada, USA DETC007-34433

More information

Mirror shape recovery from image curves and intrinsic parameters: Rotationally symmetric and conic mirrors. Abstract. 2. Mirror shape recovery

Mirror shape recovery from image curves and intrinsic parameters: Rotationally symmetric and conic mirrors. Abstract. 2. Mirror shape recovery Mirror hape recovery from image curve and intrinic parameter: Rotationally ymmetric and conic mirror Nuno Gonçalve and Helder Araújo Λ Intitute of Sytem and Robotic Univerity of Coimbra Pinhal de Marroco

More information

DAROS: Distributed User-Server Assignment And Replication For Online Social Networking Applications

DAROS: Distributed User-Server Assignment And Replication For Online Social Networking Applications DAROS: Ditributed Uer-Server Aignment And Replication For Online Social Networking Application Thuan Duong-Ba School of EECS Oregon State Univerity Corvalli, OR 97330, USA Email: duongba@eec.oregontate.edu

More information

Motivation: Level Sets. Input Data Noisy. Easy Case Use Marching Cubes. Intensity Varies. Non-uniform Exposure. Roger Crawfis

Motivation: Level Sets. Input Data Noisy. Easy Case Use Marching Cubes. Intensity Varies. Non-uniform Exposure. Roger Crawfis Level Set Motivation: Roger Crawfi Slide collected from: Fan Ding, Charle Dyer, Donald Tanguay and Roger Crawfi 4/24/2003 R. Crawfi, Ohio State Univ. 109 Eay Cae Ue Marching Cube Input Data Noiy 4/24/2003

More information

UC Berkeley International Conference on GIScience Short Paper Proceedings

UC Berkeley International Conference on GIScience Short Paper Proceedings UC Berkeley International Conference on GIScience Short Paper Proceeding Title A novel method for probabilitic coverage etimation of enor network baed on 3D vector repreentation in complex urban environment

More information

Stochastic Search and Graph Techniques for MCM Path Planning Christine D. Piatko, Christopher P. Diehl, Paul McNamee, Cheryl Resch and I-Jeng Wang

Stochastic Search and Graph Techniques for MCM Path Planning Christine D. Piatko, Christopher P. Diehl, Paul McNamee, Cheryl Resch and I-Jeng Wang Stochatic Search and Graph Technique for MCM Path Planning Chritine D. Piatko, Chritopher P. Diehl, Paul McNamee, Cheryl Rech and I-Jeng Wang The John Hopkin Univerity Applied Phyic Laboratory, Laurel,

More information

Routing Definition 4.1

Routing Definition 4.1 4 Routing So far, we have only looked at network without dealing with the iue of how to end information in them from one node to another The problem of ending information in a network i known a routing

More information

MAT 155: Describing, Exploring, and Comparing Data Page 1 of NotesCh2-3.doc

MAT 155: Describing, Exploring, and Comparing Data Page 1 of NotesCh2-3.doc MAT 155: Decribing, Exploring, and Comparing Data Page 1 of 8 001-oteCh-3.doc ote for Chapter Summarizing and Graphing Data Chapter 3 Decribing, Exploring, and Comparing Data Frequency Ditribution, Graphic

More information

Laboratory Exercise 6

Laboratory Exercise 6 Laboratory Exercie 6 Adder, Subtractor, and Multiplier a a The purpoe of thi exercie i to examine arithmetic circuit that add, ubtract, and multiply number. Each b c circuit will be decribed in Verilog

More information

Minimum congestion spanning trees in bipartite and random graphs

Minimum congestion spanning trees in bipartite and random graphs Minimum congetion panning tree in bipartite and random graph M.I. Otrovkii Department of Mathematic and Computer Science St. John Univerity 8000 Utopia Parkway Queen, NY 11439, USA e-mail: otrovm@tjohn.edu

More information

Floating Point CORDIC Based Power Operation

Floating Point CORDIC Based Power Operation Floating Point CORDIC Baed Power Operation Kazumi Malhan, Padmaja AVL Electrical and Computer Engineering Department School of Engineering and Computer Science Oakland Univerity, Rocheter, MI e-mail: kmalhan@oakland.edu,

More information

Lecture 14: Minimum Spanning Tree I

Lecture 14: Minimum Spanning Tree I COMPSCI 0: Deign and Analyi of Algorithm October 4, 07 Lecture 4: Minimum Spanning Tree I Lecturer: Rong Ge Scribe: Fred Zhang Overview Thi lecture we finih our dicuion of the hortet path problem and introduce

More information

3D SMAP Algorithm. April 11, 2012

3D SMAP Algorithm. April 11, 2012 3D SMAP Algorithm April 11, 2012 Baed on the original SMAP paper [1]. Thi report extend the tructure of MSRF into 3D. The prior ditribution i modified to atify the MRF property. In addition, an iterative

More information

Laboratory Exercise 2

Laboratory Exercise 2 Laoratory Exercie Numer and Diplay Thi i an exercie in deigning cominational circuit that can perform inary-to-decimal numer converion and inary-coded-decimal (BCD) addition. Part I We wih to diplay on

More information

1 The secretary problem

1 The secretary problem Thi i new material: if you ee error, pleae email jtyu at tanford dot edu 1 The ecretary problem We will tart by analyzing the expected runtime of an algorithm, a you will be expected to do on your homework.

More information

HOMEWORK #3 BME 473 ~ Applied Biomechanics Due during Week #10

HOMEWORK #3 BME 473 ~ Applied Biomechanics Due during Week #10 HOMEWORK #3 BME 473 ~ Applied Biomechanic Due during Week #1 1. We dicued different angle et convention in cla. One common convention i a Bod-fied X-Y-Z rotation equence. With thi convention, the B frame

More information

Computer Aided Drafting, Design and Manufacturing Volume 25, Number 3, September 2015, Page 10

Computer Aided Drafting, Design and Manufacturing Volume 25, Number 3, September 2015, Page 10 Computer Aided Drafting, Deign and Manufacturing Volume 5, umber 3, September 015, Page 10 CADDM Reearch of atural Geture Recognition and Interactive Technology Compatible with YCbCr and SV Color Space

More information

Representations and Transformations. Objectives

Representations and Transformations. Objectives Repreentation and Tranformation Objective Derive homogeneou coordinate tranformation matrice Introduce tandard tranformation - Rotation - Tranlation - Scaling - Shear Scalar, Point, Vector Three baic element

More information

Topics. Lecture 37: Global Optimization. Issues. A Simple Example: Copy Propagation X := 3 B > 0 Y := 0 X := 4 Y := Z + W A := 2 * 3X

Topics. Lecture 37: Global Optimization. Issues. A Simple Example: Copy Propagation X := 3 B > 0 Y := 0 X := 4 Y := Z + W A := 2 * 3X Lecture 37: Global Optimization [Adapted from note by R. Bodik and G. Necula] Topic Global optimization refer to program optimization that encompa multiple baic block in a function. (I have ued the term

More information

A SIMPLE IMPERATIVE LANGUAGE THE STORE FUNCTION NON-TERMINATING COMMANDS

A SIMPLE IMPERATIVE LANGUAGE THE STORE FUNCTION NON-TERMINATING COMMANDS A SIMPLE IMPERATIVE LANGUAGE Eventually we will preent the emantic of a full-blown language, with declaration, type and looping. However, there are many complication, o we will build up lowly. Our firt

More information

Performance of a Robust Filter-based Approach for Contour Detection in Wireless Sensor Networks

Performance of a Robust Filter-based Approach for Contour Detection in Wireless Sensor Networks Performance of a Robut Filter-baed Approach for Contour Detection in Wirele Senor Network Hadi Alati, William A. Armtrong, Jr., and Ai Naipuri Department of Electrical and Computer Engineering The Univerity

More information

Laboratory Exercise 6

Laboratory Exercise 6 Laboratory Exercie 6 Adder, Subtractor, and Multiplier The purpoe of thi exercie i to examine arithmetic circuit that add, ubtract, and multiply number. Each circuit will be decribed in Verilog and implemented

More information

CENTER-POINT MODEL OF DEFORMABLE SURFACE

CENTER-POINT MODEL OF DEFORMABLE SURFACE CENTER-POINT MODEL OF DEFORMABLE SURFACE Piotr M. Szczypinki Iintitute of Electronic, Technical Univerity of Lodz, Poland Abtract: Key word: Center-point model of deformable urface for egmentation of 3D

More information

1 Vehicle Attitude in Euler Angle Form. Kinematics 3: Kinematic Models of Sensors and Actuators

1 Vehicle Attitude in Euler Angle Form. Kinematics 3: Kinematic Models of Sensors and Actuators 1.1Axi Convention 1 Kinematic 3: Kinematic Model of Senor and Actuator 1 Vehicle Attitude in Euler Angle Form 1.1 Axi Convention In aeropace vehicle, z point downward. Good for airplane and atellite. Here

More information

Algorithmic Discrete Mathematics 4. Exercise Sheet

Algorithmic Discrete Mathematics 4. Exercise Sheet Algorithmic Dicrete Mathematic. Exercie Sheet Department of Mathematic SS 0 PD Dr. Ulf Lorenz 0. and. May 0 Dipl.-Math. David Meffert Verion of May, 0 Groupwork Exercie G (Shortet path I) (a) Calculate

More information

Focused Video Estimation from Defocused Video Sequences

Focused Video Estimation from Defocused Video Sequences Focued Video Etimation from Defocued Video Sequence Junlan Yang a, Dan Schonfeld a and Magdi Mohamed b a Multimedia Communication Lab, ECE Dept., Univerity of Illinoi, Chicago, IL b Phyical Realization

More information

else end while End References

else end while End References 621-630. [RM89] [SK76] Roenfeld, A. and Melter, R. A., Digital geometry, The Mathematical Intelligencer, vol. 11, No. 3, 1989, pp. 69-72. Sklanky, J. and Kibler, D. F., A theory of nonuniformly digitized

More information

Planning of scooping position and approach path for loading operation by wheel loader

Planning of scooping position and approach path for loading operation by wheel loader 22 nd International Sympoium on Automation and Robotic in Contruction ISARC 25 - September 11-14, 25, Ferrara (Italy) 1 Planning of cooping poition and approach path for loading operation by wheel loader

More information

Hassan Ghaziri AUB, OSB Beirut, Lebanon Key words Competitive self-organizing maps, Meta-heuristics, Vehicle routing problem,

Hassan Ghaziri AUB, OSB Beirut, Lebanon Key words Competitive self-organizing maps, Meta-heuristics, Vehicle routing problem, COMPETITIVE PROBABIISTIC SEF-ORGANIZING MAPS FOR ROUTING PROBEMS Haan Ghaziri AUB, OSB Beirut, ebanon ghaziri@aub.edu.lb Abtract In thi paper, we have applied the concept of the elf-organizing map (SOM)

More information

Shortest Paths with Single-Point Visibility Constraint

Shortest Paths with Single-Point Visibility Constraint Shortet Path with Single-Point Viibility Contraint Ramtin Khoravi Mohammad Ghodi Department of Computer Engineering Sharif Univerity of Technology Abtract Thi paper tudie the problem of finding a hortet

More information

FPGA Implementation of Closed Loop Control of Pan Tilt Mechanism

FPGA Implementation of Closed Loop Control of Pan Tilt Mechanism IJCTA, 9(39), 206, pp. 295-302 International Science Pre Cloed Loop Control of Soft Switched Forward Converter Uing Intelligent Controller 295 FPGA Implementation of Cloed Loop Control of Pan Tilt Mechanim

More information

Shading. Reading. Pinhole camera. Basic 3D graphics. Brian Curless CSE 457 Spring 2017

Shading. Reading. Pinhole camera. Basic 3D graphics. Brian Curless CSE 457 Spring 2017 Reading Optional: Angel and Shreiner: chapter 5. Marchner and Shirley: chapter 0, chapter 7. Shading Further reading: OpenGL red book, chapter 5. Brian Curle CSE 457 Spring 207 2 Baic 3D graphic With affine

More information

IMPLEMENTATION OF AREA, VOLUME AND LINE SOURCES

IMPLEMENTATION OF AREA, VOLUME AND LINE SOURCES December 01 ADMS 5 P503I1 IMPEMENTATION OF AREA, VOUME AND INE SOURCES The Met. Office (D J Thomon) and CERC 1. INTRODUCTION ADMS model line ource, and area and volume ource with conve polgon bae area.

More information

An Active Stereo Vision System Based on Neural Pathways of Human Binocular Motor System

An Active Stereo Vision System Based on Neural Pathways of Human Binocular Motor System Journal of Bionic Engineering 4 (2007) 185 192 An Active Stereo Viion Sytem Baed on Neural Pathway of Human Binocular Motor Sytem Yu-zhang Gu 1, Makoto Sato 2, Xiao-lin Zhang 2 1. Department of Advanced

More information

Anisotropic filtering on normal field and curvature tensor field using optimal estimation theory

Anisotropic filtering on normal field and curvature tensor field using optimal estimation theory Aniotropic filtering on normal field and curvature tenor field uing optimal etimation theory Min Liu Yuhen Liu and Karthik Ramani Purdue Univerity, Wet Lafayette, Indiana, USA Email: {liu66 liu28 ramani}@purdue.edu

More information

AN ALGORITHM FOR RESTRICTED NORMAL FORM TO SOLVE DUAL TYPE NON-CANONICAL LINEAR FRACTIONAL PROGRAMMING PROBLEM

AN ALGORITHM FOR RESTRICTED NORMAL FORM TO SOLVE DUAL TYPE NON-CANONICAL LINEAR FRACTIONAL PROGRAMMING PROBLEM RAC Univerity Journal, Vol IV, No, 7, pp 87-9 AN ALGORITHM FOR RESTRICTED NORMAL FORM TO SOLVE DUAL TYPE NON-CANONICAL LINEAR FRACTIONAL PROGRAMMING PROLEM Mozzem Hoain Department of Mathematic Ghior Govt

More information

(12) Patent Application Publication (10) Pub. No.: US 2011/ A1

(12) Patent Application Publication (10) Pub. No.: US 2011/ A1 (19) United State US 2011 0316690A1 (12) Patent Application Publication (10) Pub. No.: US 2011/0316690 A1 Siegman (43) Pub. Date: Dec. 29, 2011 (54) SYSTEMAND METHOD FOR IDENTIFYING ELECTRICAL EQUIPMENT

More information

/06/$ IEEE 364

/06/$ IEEE 364 006 IEEE International ympoium on ignal Proceing and Information Technology oie Variance Etimation In ignal Proceing David Makovoz IPAC, California Intitute of Technology, MC-0, Paadena, CA, 95 davidm@ipac.caltech.edu;

More information

SIMIT 7. Component Type Editor (CTE) User manual. Siemens Industrial

SIMIT 7. Component Type Editor (CTE) User manual. Siemens Industrial SIMIT 7 Component Type Editor (CTE) Uer manual Siemen Indutrial Edition January 2013 Siemen offer imulation oftware to plan, imulate and optimize plant and machine. The imulation- and optimizationreult

More information

Edits in Xylia Validity Preserving Editing of XML Documents

Edits in Xylia Validity Preserving Editing of XML Documents dit in Xylia Validity Preerving diting of XML Document Pouria Shaker, Theodore S. Norvell, and Denni K. Peter Faculty of ngineering and Applied Science, Memorial Univerity of Newfoundland, St. John, NFLD,

More information

PERFORMANCE EVALUATION OF TRANSMISSION DISTANCE AND BIT RATES IN INTER-SATELLITE OPTICAL WIRELESS COMMUNICATION SYSTEM

PERFORMANCE EVALUATION OF TRANSMISSION DISTANCE AND BIT RATES IN INTER-SATELLITE OPTICAL WIRELESS COMMUNICATION SYSTEM PERFORMANCE EVALUATION OF TRANSMISSION DISTANCE AND BIT RATES IN INTER-SATELLITE OPTICAL WIRELESS COMMUNICATION SYSTEM Rohni Joy 1, Ami Lavingia 2, Prof. Kruti Lavingia 3 1 Electronic and Communication

More information

Key Terms - MinMin, MaxMin, Sufferage, Task Scheduling, Standard Deviation, Load Balancing.

Key Terms - MinMin, MaxMin, Sufferage, Task Scheduling, Standard Deviation, Load Balancing. Volume 3, Iue 11, November 2013 ISSN: 2277 128X International Journal of Advanced Reearch in Computer Science and Software Engineering Reearch Paper Available online at: www.ijarce.com Tak Aignment in

More information

xy-monotone path existence queries in a rectilinear environment

xy-monotone path existence queries in a rectilinear environment CCCG 2012, Charlottetown, P.E.I., Augut 8 10, 2012 xy-monotone path exitence querie in a rectilinear environment Gregory Bint Anil Mahehwari Michiel Smid Abtract Given a planar environment coniting of

More information

Markov Random Fields in Image Segmentation

Markov Random Fields in Image Segmentation Preented at SSIP 2011, Szeged, Hungary Markov Random Field in Image Segmentation Zoltan Kato Image Proceing & Computer Graphic Dept. Univerity of Szeged Hungary Zoltan Kato: Markov Random Field in Image

More information

Shading. Reading. Pinhole camera. Basic 3D graphics. Brian Curless CSE 457 Spring Required: Angel chapter 5.

Shading. Reading. Pinhole camera. Basic 3D graphics. Brian Curless CSE 457 Spring Required: Angel chapter 5. Reading Required: Angel chapter 5. Shading Optional: OpenGL red book, chapter 5. Brian Curle CSE 457 Spring 2015 1 2 Baic 3D graphic With affine matrice, we can now tranform virtual 3D object in their

More information

( ) subject to m. e (2) L are 2L+1. = s SEG SEG Las Vegas 2012 Annual Meeting Page 1

( ) subject to m. e (2) L are 2L+1. = s SEG SEG Las Vegas 2012 Annual Meeting Page 1 A new imultaneou ource eparation algorithm uing frequency-divere filtering Ying Ji*, Ed Kragh, and Phil Chritie, Schlumberger Cambridge Reearch Summary We decribe a new imultaneou ource eparation algorithm

More information

Parallel MATLAB at FSU: Task Computing

Parallel MATLAB at FSU: Task Computing Parallel MATLAB at FSU: Tak John Burkardt Department of Scientific Florida State Univerity... 1:30-2:30 Thurday, 07 April 2011 499 Dirac Science Library... http://people.c.fu.edu/ jburkardt/preentation/...

More information

Compressed Sensing Image Processing Based on Stagewise Orthogonal Matching Pursuit

Compressed Sensing Image Processing Based on Stagewise Orthogonal Matching Pursuit Senor & randucer, Vol. 8, Iue 0, October 204, pp. 34-40 Senor & randucer 204 by IFSA Publihing, S. L. http://www.enorportal.com Compreed Sening Image Proceing Baed on Stagewie Orthogonal Matching Puruit

More information

Trainable Context Model for Multiscale Segmentation

Trainable Context Model for Multiscale Segmentation Trainable Context Model for Multicale Segmentation Hui Cheng and Charle A. Bouman School of Electrical and Computer Engineering Purdue Univerity Wet Lafayette, IN 47907-1285 {hui, bouman}@ ecn.purdue.edu

More information

Advanced Encryption Standard and Modes of Operation

Advanced Encryption Standard and Modes of Operation Advanced Encryption Standard and Mode of Operation G. Bertoni L. Breveglieri Foundation of Cryptography - AES pp. 1 / 50 AES Advanced Encryption Standard (AES) i a ymmetric cryptographic algorithm AES

More information

Correlation Models for Shadow Fading Simulation

Correlation Models for Shadow Fading Simulation Correlation Model for Shadow Fading Simulation IEEE 80.6 Preentation Submiion Template (Rev. 8.3) Document Number: IEEE S80.6m-07/060 Date Submitted: 007-03-3 Source: I-Kang Fu, Chi-Fang Li, E-mail: IKFu@itri.org.tw

More information

Connected Placement of Disaster Shelters in Modern Cities

Connected Placement of Disaster Shelters in Modern Cities Connected Placement of Diater Shelter in Modern Citie Huanyang Zheng and Jie Wu Department of Computer and Information Science Temple Univerity, USA {huanyang.zheng, jiewu}@temple.edu ABSTRACT Thi paper

More information

Distributed Packet Processing Architecture with Reconfigurable Hardware Accelerators for 100Gbps Forwarding Performance on Virtualized Edge Router

Distributed Packet Processing Architecture with Reconfigurable Hardware Accelerators for 100Gbps Forwarding Performance on Virtualized Edge Router Ditributed Packet Proceing Architecture with Reconfigurable Hardware Accelerator for 100Gbp Forwarding Performance on Virtualized Edge Router Satohi Nihiyama, Hitohi Kaneko, and Ichiro Kudo Abtract To

More information

CSE 252B: Computer Vision II

CSE 252B: Computer Vision II CSE 252B: Computer Vision II Lecturer: Serge Belongie Scribe: Sameer Agarwal LECTURE 1 Image Formation 1.1. The geometry of image formation We begin by considering the process of image formation when a

More information

The Data Locality of Work Stealing

The Data Locality of Work Stealing The Data Locality of Work Stealing Umut A. Acar School of Computer Science Carnegie Mellon Univerity umut@c.cmu.edu Guy E. Blelloch School of Computer Science Carnegie Mellon Univerity guyb@c.cmu.edu Robert

More information

A System Dynamics Model for Transient Availability Modeling of Repairable Redundant Systems

A System Dynamics Model for Transient Availability Modeling of Repairable Redundant Systems International Journal of Performability Engineering Vol., No. 3, May 05, pp. 03-. RAMS Conultant Printed in India A Sytem Dynamic Model for Tranient Availability Modeling of Repairable Redundant Sytem

More information

Delaunay Triangulation: Incremental Construction

Delaunay Triangulation: Incremental Construction Chapter 6 Delaunay Triangulation: Incremental Contruction In the lat lecture, we have learned about the Lawon ip algorithm that compute a Delaunay triangulation of a given n-point et P R 2 with O(n 2 )

More information

AUTOMATIC TEST CASE GENERATION USING UML MODELS

AUTOMATIC TEST CASE GENERATION USING UML MODELS Volume-2, Iue-6, June-2014 AUTOMATIC TEST CASE GENERATION USING UML MODELS 1 SAGARKUMAR P. JAIN, 2 KHUSHBOO S. LALWANI, 3 NIKITA K. MAHAJAN, 4 BHAGYASHREE J. GADEKAR 1,2,3,4 Department of Computer Engineering,

More information

Note 2: Transformation (modeling and viewing)

Note 2: Transformation (modeling and viewing) Note : Tranformation (modeling and viewing Reading: tetbook chapter 4 (geometric tranformation and chapter 5 (viewing.. Introduction (model tranformation modeling coordinate modeling tranformation world

More information

Geometry Inspired Algorithms for Linear Programming

Geometry Inspired Algorithms for Linear Programming Geoetry Inpired Algorith or Linear Prograing Dhananjay P. Mehendale Sir Parahurabhau College, Tilak Road, Pune-4030, India Abtract In thi paper we dicu oe novel algorith or linear prograing inpired by

More information

On successive packing approach to multidimensional (M-D) interleaving

On successive packing approach to multidimensional (M-D) interleaving On ucceive packing approach to multidimenional (M-D) interleaving Xi Min Zhang Yun Q. hi ankar Bau Abtract We propoe an interleaving cheme for multidimenional (M-D) interleaving. To achieved by uing a

More information

A Linear Interpolation-Based Algorithm for Path Planning and Replanning on Girds *

A Linear Interpolation-Based Algorithm for Path Planning and Replanning on Girds * Advance in Linear Algebra & Matrix Theory, 2012, 2, 20-24 http://dx.doi.org/10.4236/alamt.2012.22003 Publihed Online June 2012 (http://www.scirp.org/journal/alamt) A Linear Interpolation-Baed Algorithm

More information

Shortest Paths Problem. CS 362, Lecture 20. Today s Outline. Negative Weights

Shortest Paths Problem. CS 362, Lecture 20. Today s Outline. Negative Weights Shortet Path Problem CS 6, Lecture Jared Saia Univerity of New Mexico Another intereting problem for graph i that of finding hortet path Aume we are given a weighted directed graph G = (V, E) with two

More information

A Practical Model for Minimizing Waiting Time in a Transit Network

A Practical Model for Minimizing Waiting Time in a Transit Network A Practical Model for Minimizing Waiting Time in a Tranit Network Leila Dianat, MASc, Department of Civil Engineering, Sharif Univerity of Technology, Tehran, Iran Youef Shafahi, Ph.D. Aociate Profeor,

More information

Increasing Throughput and Reducing Delay in Wireless Sensor Networks Using Interference Alignment

Increasing Throughput and Reducing Delay in Wireless Sensor Networks Using Interference Alignment Int. J. Communication, Network and Sytem Science, 0, 5, 90-97 http://dx.doi.org/0.436/ijcn.0.50 Publihed Online February 0 (http://www.scirp.org/journal/ijcn) Increaing Throughput and Reducing Delay in

More information

A note on degenerate and spectrally degenerate graphs

A note on degenerate and spectrally degenerate graphs A note on degenerate and pectrally degenerate graph Noga Alon Abtract A graph G i called pectrally d-degenerate if the larget eigenvalue of each ubgraph of it with maximum degree D i at mot dd. We prove

More information

Touring a Sequence of Polygons

Touring a Sequence of Polygons Touring a Sequence of Polygon Mohe Dror (1) Alon Efrat (1) Anna Lubiw (2) Joe Mitchell (3) (1) Univerity of Arizona (2) Univerity of Waterloo (3) Stony Brook Univerity Problem: Given a equence of k polygon

More information

A Multi-objective Genetic Algorithm for Reliability Optimization Problem

A Multi-objective Genetic Algorithm for Reliability Optimization Problem International Journal of Performability Engineering, Vol. 5, No. 3, April 2009, pp. 227-234. RAMS Conultant Printed in India A Multi-objective Genetic Algorithm for Reliability Optimization Problem AMAR

More information

Tracking High Speed Skater by Using Multiple Model

Tracking High Speed Skater by Using Multiple Model Vol. 2, No. 26 Tracing High Speed Sater by Uing Multiple Model Guojun Liu & Xianglong Tang School of Computer Science & Engineering Harbin Intitute of Technology Harbin 5000, China E-mail: hitliu@hit.edu.cn

More information

A PROBABILISTIC NOTION OF CAMERA GEOMETRY: CALIBRATED VS. UNCALIBRATED

A PROBABILISTIC NOTION OF CAMERA GEOMETRY: CALIBRATED VS. UNCALIBRATED A PROBABILISTIC NOTION OF CAMERA GEOMETRY: CALIBRATED VS. UNCALIBRATED Jutin Domke and Yianni Aloimono Computational Viion Laboratory, Center for Automation Reearch Univerity of Maryland College Park,

More information

np vp cost = 0 cost = c np vp cost = c I replacing term cost = c+c n cost = c * Error detection Error correction pron det pron det n gi

np vp cost = 0 cost = c np vp cost = c I replacing term cost = c+c n cost = c * Error detection Error correction pron det pron det n gi Spoken Language Paring with Robutne and ncrementality Yohihide Kato, Shigeki Matubara, Katuhiko Toyama and Yauyohi nagaki y Graduate School of Engineering, Nagoya Univerity y Faculty of Language and Culture,

More information

Aalborg Universitet. Published in: Proceedings of the Working Conference on Advanced Visual Interfaces

Aalborg Universitet. Published in: Proceedings of the Working Conference on Advanced Visual Interfaces Aalborg Univeritet Software-Baed Adjutment of Mobile Autotereocopic Graphic Uing Static Parallax Barrier Paprocki, Martin Marko; Krog, Kim Srirat; Kritofferen, Morten Bak; Krau, Martin Publihed in: Proceeding

More information

CERIAS Tech Report EFFICIENT PARALLEL ALGORITHMS FOR PLANAR st-graphs. by Mikhail J. Atallah, Danny Z. Chen, and Ovidiu Daescu

CERIAS Tech Report EFFICIENT PARALLEL ALGORITHMS FOR PLANAR st-graphs. by Mikhail J. Atallah, Danny Z. Chen, and Ovidiu Daescu CERIAS Tech Report 2003-15 EFFICIENT PARALLEL ALGORITHMS FOR PLANAR t-graphs by Mikhail J. Atallah, Danny Z. Chen, and Ovidiu Daecu Center for Education and Reearch in Information Aurance and Security,

More information

New Structural Decomposition Techniques for Constraint Satisfaction Problems

New Structural Decomposition Techniques for Constraint Satisfaction Problems New Structural Decompoition Technique for Contraint Satifaction Problem Yaling Zheng and Berthe Y. Choueiry Contraint Sytem Laboratory Univerity of Nebraka-Lincoln Email: yzheng choueiry@ce.unl.edu Abtract.

More information

A METHOD OF REAL-TIME NURBS INTERPOLATION WITH CONFINED CHORD ERROR FOR CNC SYSTEMS

A METHOD OF REAL-TIME NURBS INTERPOLATION WITH CONFINED CHORD ERROR FOR CNC SYSTEMS Vietnam Journal of Science and Technology 55 (5) (017) 650-657 DOI: 10.1565/55-518/55/5/906 A METHOD OF REAL-TIME NURBS INTERPOLATION WITH CONFINED CHORD ERROR FOR CNC SYSTEMS Nguyen Huu Quang *, Banh

More information

Touring a Sequence of Polygons

Touring a Sequence of Polygons Touring a Sequence of Polygon Mohe Dror (1) Alon Efrat (1) Anna Lubiw (2) Joe Mitchell (3) (1) Univerity of Arizona (2) Univerity of Waterloo (3) Stony Brook Univerity Problem: Given a equence of k polygon

More information

Orienting Micro-Scale Parts with Squeeze and Roll Primitives

Orienting Micro-Scale Parts with Squeeze and Roll Primitives Orienting Micro-Scale Part with Squeeze and Roll Primitive Mark Moll Michael A. Erdmann Ron Fearing Ken Goldberg mmoll@c.cmu.edu me@c.cmu.edu ronf@eec.berkeley.edu goldberg@ieor.berkeley.edu Department

More information

Analysis of Surface Wave Propagation Based on the Thin Layered Element Method

Analysis of Surface Wave Propagation Based on the Thin Layered Element Method ABSTACT : Analyi of Surface Wave Propagation Baed on the Thin ayered Element Method H. AKAGAWA 1 and S. AKAI 1 Engineer, Technical Centre, Oyo Corporation, Ibaraki, Japan Profeor, Graduate School of Engineering,

More information

All in-focus View Synthesis from Under-Sampled Light Fields

All in-focus View Synthesis from Under-Sampled Light Fields ICAT 2003 December 3-5, Tokyo, Japan All in-focu View Synthei from Under-Sampled Light Field Keita Takahahi,AkiraKubota and Takehi Naemura TheUniverityofTokyo Carnegie Mellon Univerity 7-3-1, Hongo, Bunkyo-ku,

More information

Lecture 17: Shortest Paths

Lecture 17: Shortest Paths Lecture 7: Shortet Path CSE 373: Data Structure and Algorithm CSE 373 9 WI - KASEY CHAMPION Adminitrivia How to Ace the Technical Interview Seion today! - 6-8pm - Sieg 34 No BS CS Career Talk Thurday -

More information

ADAM - A PROBLEM-ORIENTED SYMBOL PROCESSOR

ADAM - A PROBLEM-ORIENTED SYMBOL PROCESSOR ADAM - A PROBLEM-ORIENTED SYMBOL PROCESSOR A. P. Mullery and R. F. Schauer Thoma J. Waton Reearch Center International Buine Machine Corporation Yorktown Height, New York R. Rice International Buine Machine

More information

INVERSE DYNAMIC SIMULATION OF A HYDRAULIC DRIVE WITH MODELICA. α Cylinder chamber areas ratio... σ Viscous friction coefficient

INVERSE DYNAMIC SIMULATION OF A HYDRAULIC DRIVE WITH MODELICA. α Cylinder chamber areas ratio... σ Viscous friction coefficient Proceeding of the ASME 2013 International Mechanical Engineering Congre & Expoition IMECE2013 November 15-21, 2013, San Diego, California, USA IMECE2013-63310 INVERSE DYNAMIC SIMULATION OF A HYDRAULIC

More information

Today s Outline. CS 561, Lecture 23. Negative Weights. Shortest Paths Problem. The presence of a negative cycle might mean that there is

Today s Outline. CS 561, Lecture 23. Negative Weights. Shortest Paths Problem. The presence of a negative cycle might mean that there is Today Outline CS 56, Lecture Jared Saia Univerity of New Mexico The path that can be trodden i not the enduring and unchanging Path. The name that can be named i not the enduring and unchanging Name. -

More information

Kinematics Programming for Cooperating Robotic Systems

Kinematics Programming for Cooperating Robotic Systems Kinematic Programming for Cooperating Robotic Sytem Critiane P. Tonetto, Carlo R. Rocha, Henrique Sima, Altamir Dia Federal Univerity of Santa Catarina, Mechanical Engineering Department, P.O. Box 476,

More information

Karen L. Collins. Wesleyan University. Middletown, CT and. Mark Hovey MIT. Cambridge, MA Abstract

Karen L. Collins. Wesleyan University. Middletown, CT and. Mark Hovey MIT. Cambridge, MA Abstract Mot Graph are Edge-Cordial Karen L. Collin Dept. of Mathematic Weleyan Univerity Middletown, CT 6457 and Mark Hovey Dept. of Mathematic MIT Cambridge, MA 239 Abtract We extend the definition of edge-cordial

More information

RESEARCH ON SAR IMAGE MATCHING TECHNOLOGY BASED ON SIFT

RESEARCH ON SAR IMAGE MATCHING TECHNOLOGY BASED ON SIFT RESEARCH ON SAR IMAGE MATCHING TECHNOLOGY BASED ON SIFT LIU Jing-zheng, YU Xu-chu Zhengzhou Intitute of Surveying and Mapping, 66 Longhai Road, Zhengzhou 45005,China-ljzchxy@63.com Commiion I, WG I/ KEY

More information

USING ARTIFICIAL NEURAL NETWORKS TO APPROXIMATE A DISCRETE EVENT STOCHASTIC SIMULATION MODEL

USING ARTIFICIAL NEURAL NETWORKS TO APPROXIMATE A DISCRETE EVENT STOCHASTIC SIMULATION MODEL USING ARTIFICIAL NEURAL NETWORKS TO APPROXIMATE A DISCRETE EVENT STOCHASTIC SIMULATION MODEL Robert A. Kilmer Department of Sytem Engineering Unite State Military Acaemy Wet Point, NY 1996 Alice E. Smith

More information

Lecture Outline. Global flow analysis. Global Optimization. Global constant propagation. Liveness analysis. Local Optimization. Global Optimization

Lecture Outline. Global flow analysis. Global Optimization. Global constant propagation. Liveness analysis. Local Optimization. Global Optimization Lecture Outline Global flow analyi Global Optimization Global contant propagation Livene analyi Adapted from Lecture by Prof. Alex Aiken and George Necula (UCB) CS781(Praad) L27OP 1 CS781(Praad) L27OP

More information

A Load Balancing Model based on Load-aware for Distributed Controllers. Fengjun Shang, Wenjuan Gong

A Load Balancing Model based on Load-aware for Distributed Controllers. Fengjun Shang, Wenjuan Gong 4th International Conference on Machinery, Material and Computing Technology (ICMMCT 2016) A Load Balancing Model baed on Load-aware for Ditributed Controller Fengjun Shang, Wenjuan Gong College of Compute

More information

TAM 212 Worksheet 3. Solutions

TAM 212 Worksheet 3. Solutions Name: Group member: TAM 212 Workheet 3 Solution The workheet i concerned with the deign of the loop-the-loop for a roller coater ytem. Old loop deign: The firt generation of loop wa circular, a hown below.

More information

CSE 250B Assignment 4 Report

CSE 250B Assignment 4 Report CSE 250B Aignment 4 Report March 24, 2012 Yuncong Chen yuncong@c.ucd.edu Pengfei Chen pec008@ucd.edu Yang Liu yal060@c.ucd.edu Abtract In thi project, we implemented the recurive autoencoder (RAE) a decribed

More information

Data Mining with Linguistic Thresholds

Data Mining with Linguistic Thresholds Int. J. Contemp. Math. Science, Vol. 7, 22, no. 35, 7-725 Data Mining with Linguitic Threhold Tzung-Pei Hong Department of Electrical Engineering National Univerity of Kaohiung Kaohiung, Taiwan, R.O.C.

More information

CSE152a Computer Vision Assignment 1 WI14 Instructor: Prof. David Kriegman. Revision 0

CSE152a Computer Vision Assignment 1 WI14 Instructor: Prof. David Kriegman. Revision 0 CSE152a Computer Vision Assignment 1 WI14 Instructor: Prof. David Kriegman. Revision Instructions: This assignment should be solved, and written up in groups of 2. Work alone only if you can not find a

More information