Where am I? Using Vanishing Points

Size: px
Start display at page:

Download "Where am I? Using Vanishing Points"

Transcription

1 Whee am I? Using Vanishing Points

2 Vanishing point Vanishing line fo hoizon Vanishing point What can vanishing line tell us about me? Hoizon Camea pitch angle (looking down) Camea oll angle (tilted towad ight)

3 Whee am I w..t. Gound Plane? Camea u v 1 X Y K t C W Z 1 How to compute?

4 What can a Vanishing Point tell us about? Camea v

5 What can a Vanishing Point tell us about? Camea Z 1 v

6 What can a Vanishing Point tell us about? Camea Z 1 1 C v K t W 1 v

7 Single Vanishing Point Camea K -1 v 3 Z 1 1 C v K t W 1 v K 3 v

8 Single Vanishing Point Camea K -1 v 3 Z 1 1 C v K t W 1 v K 3 Kv because 3 is a unit vecto. Kv Z vanishing point tells us about the suface nomal of the gound plane v

9 Single Vanishing Point Camea K -1 v 3 Z 1 1 C v K t W 1 v K 3 Kv because 3 is a unit vecto. Kv Z vanishing point tells us about the suface nomal of the gound plane Rotation ambiguity v

10 Single Vanishing Point Camea Kv -1 Kv 3-1 K -1 v 3 Z 1 1 Roll and pitch angle can be computed by the gound plane. v

11 Single Vanishing Point Camea Kv -1 Kv 3-1 K -1 v 3 Z 1 1 Roll and pitch angle can be computed by the gound plane. 3D spatial otation: a sequence of Eule angle otation (oll/pitch/yaw). v

12 Single Vanishing Point Camea Kv -1 Kv 3-1 K -1 v 3 Z 1 1 Roll and pitch angle can be computed by the gound plane. Yaw: otation about z axis: R yaw cos -sin sin cos 1 v

13 Single Vanishing Point Camea Kv -1 Kv 3-1 K -1 v 3 Z 1 1 Roll and pitch angle can be computed by the gound plane. Yaw: otation about z axis: R yaw Pitch: otation about y axis: Rpitch cos -sin sin cos 1 cos sin 1 -sin cos v

14 Single Vanishing Point Camea Kv -1 Kv 3-1 K -1 v 3 Z 1 1 Roll and pitch angle can be computed by the gound plane. Yaw: otation about z axis: R yaw Pitch: otation about y axis: Rpitch cos -sin sin cos 1 cos sin 1 -sin cos Roll: otation about x axis: R oll 1 cos -sin sin cos v

15 Single Vanishing Point Camea Kv -1 Kv 3-1 K -1 v 3 Z 1 1 Roll and pitch angle can be computed by the gound plane. Yaw: otation about z axis: R yaw Pitch: otation about y axis: Rpitch cos -sin sin cos 1 cos sin 1 -sin cos Roll: otation about x axis: R oll 1 cos -sin sin cos v -sin T yaw pitch oll cos sin R R R cos cos

16 Single Vanishing Point Camea Kv -1 Kv 3-1 K -1 v 3 Z 1 1 Roll and pitch angle can be computed by the gound plane. -sin T yaw pitch oll cos sin R R R cos cos Pitch: Roll: tan tan v

17 Single Vanishing Point (Execise) ComputeCameaUsingVanishingPoint.m f = 1224; K = [f size(im,2)/2; f size(im,1)/2; 1]; m1 = [2563;25;1]; m2 = [2439;545;1]; m3 = [571;25;1]; m4 = [723;498;1]; l1 = GetLineFomTwoPoints(m1,m2); l2 = GetLineFomTwoPoints(m3,m4); v1 = GetPointFomTwoLines(l1,l2); v1 = v1/v1(3); 3 = inv(k)*v1/nom(inv(k)*v1) pitch = atan(-3(1)/nom(3(2:3))) oll = atan(3(2)/3(3)) 3 = pitch =.736 oll = 1.116

18 Two Vanishing Points Camea v Y v X

19 Two Vanishing Points Camea X 1 v Y v X Y 1

20 Two Vanishing Points Camea X 1 C v X K t W X K 1 v Y v X Y 1

21 v Y Camea Two Vanishing Points v X X Y 1 1 C v X K t W X K 1 C v Y K t W Y K 2

22 v Y Camea Two Vanishing Points 1 X C v X K t W X 3 K v X Y 1 C v Y K t W Y K v K v -1-1 X 1, -1 2 K v X -1 1 K K v Y Y : Othogonality constaint

23 Geometic Intepetation -1 KvX X 1

24 Geometic Intepetation -1 KvX X 1-1 KvY Y 1

25 Geometic Intepetation -1 KvX X 1-1 KvY Y 1

26 Geometic Intepetation K v K v -1-1 X Y -1 KvX X 1-1 KvY Y 1

27 Geometic Intepetation (Tanslation Ambiguity)

28 Geometic Intepetation (Tanslation Ambiguity)

29 Geometic Intepetation (Tanslation Ambiguity)

30 Two Vanishing Points Camea ComputeCameaUsingTwoVanishingPoints.m f = 4; K = [f size(im,2)/2; f size(im,1)/2; 1]; v Y v X l11 = GetLineFomTwoPoints(m11,m12); l12 = GetLineFomTwoPoints(m13,m14); l21 = GetLineFomTwoPoints(m21,m22); l22 = GetLineFomTwoPoints(m23,m24); v1 = GetPointFomTwoLines(l11,l12); v2 = GetPointFomTwoLines(l21,l22); 1 = inv(k)*v1/nom(inv(k)*v1); 2 = inv(k)*v2/nom(inv(k)*v2); 3 = Vec2Skew(1)*2; R = Not othogonal matix! det(r) =.577 R *R =

31 Two Vanishing Points f = 1224; K = [f size(im,2)/2; f size(im,1)/2; 1]; ComputeCameaUsingTwoVanishingPoints.m Change focal length l11 = GetLineFomTwoPoints(m11,m12); l12 = GetLineFomTwoPoints(m13,m14); l21 = GetLineFomTwoPoints(m21,m22); l22 = GetLineFomTwoPoints(m23,m24); v1 = GetPointFomTwoLines(l11,l12); v2 = GetPointFomTwoLines(l21,l22); 1 = inv(k)*v1/nom(inv(k)*v1); 2 = inv(k)*v2/nom(inv(k)*v2); 3 = Vec2Skew(1)*2; Othogonal matix! R = det(r) =.9948 R *R =

Where am I? Using Vanishing Points

Where am I? Using Vanishing Points Whee am I? Using Vanishing Points Whee was I (how high)? Taken fom my hotel oom (6 th floo) Taken fom beach Vanishing point Vanishing line fo hoizon Vanishing point What can vanishing line tell us

More information

Coordinate Systems. Ioannis Rekleitis

Coordinate Systems. Ioannis Rekleitis Coodinate Systems Ioannis ekleitis Position epesentation Position epesentation is: P p p p x y z P CS-417 Intoduction to obotics and Intelligent Systems Oientation epesentations Descibes the otation of

More information

Prof. Feng Liu. Fall /17/2016

Prof. Feng Liu. Fall /17/2016 Pof. Feng Liu Fall 26 http://www.cs.pdx.edu/~fliu/couses/cs447/ /7/26 Last time Compositing NPR 3D Gaphics Toolkits Tansfomations 2 Today 3D Tansfomations The Viewing Pipeline Mid-tem: in class, Nov. 2

More information

Computer Graphics and Animation 3-Viewing

Computer Graphics and Animation 3-Viewing Compute Gaphics and Animation 3-Viewing Pof. D. Chales A. Wüthich, Fakultät Medien, Medieninfomatik Bauhaus-Univesität Weima caw AT medien.uni-weima.de Ma 5 Chales A. Wüthich Viewing Hee: Viewing in 3D

More information

5. Geometric Transformations and Projections

5. Geometric Transformations and Projections 5. Geometic Tansfomations and ojections 5. Tanslations and Rotations a) Tanslation d d d d d d d d b) Scaling s s s s c) Reflection (about - - lane) d) Rotation about Ais ( ) ( ) CCW 5.. Homogeneous Repesentation

More information

LOCAL GEODETIC HORIZON COORDINATES

LOCAL GEODETIC HORIZON COORDINATES LOCAL GEODETIC HOIZON COODINATES In many surveying applications it is necessary to convert geocentric Cartesian coordinates X,,Z to local geodetic horizon Cartesian coordinates E,N,U (East,North,Up). Figure

More information

A Mathematical Implementation of a Global Human Walking Model with Real-Time Kinematic Personification by Boulic, Thalmann and Thalmann.

A Mathematical Implementation of a Global Human Walking Model with Real-Time Kinematic Personification by Boulic, Thalmann and Thalmann. A Mathematical Implementation of a Global Human Walking Model with Real-Time Kinematic Pesonification by Boulic, Thalmann and Thalmann. Mashall Badley National Cente fo Physical Acoustics Univesity of

More information

3D Transformations. CS 4620 Lecture 10. Cornell CS4620 Fall 2014 Lecture Steve Marschner (with previous instructors James/Bala)

3D Transformations. CS 4620 Lecture 10. Cornell CS4620 Fall 2014 Lecture Steve Marschner (with previous instructors James/Bala) 3D Transformations CS 4620 Lecture 10 1 Translation 2 Scaling 3 Rotation about z axis 4 Rotation about x axis 5 Rotation about y axis 6 Properties of Matrices Translations: linear part is the identity

More information

CIS 580, Machine Perception, Spring 2015 Homework 1 Due: :59AM

CIS 580, Machine Perception, Spring 2015 Homework 1 Due: :59AM CIS 580, Machine Perception, Spring 2015 Homework 1 Due: 2015.02.09. 11:59AM Instructions. Submit your answers in PDF form to Canvas. This is an individual assignment. 1 Camera Model, Focal Length and

More information

3D Transformations. CS 4620 Lecture Kavita Bala w/ prior instructor Steve Marschner. Cornell CS4620 Fall 2015 Lecture 11

3D Transformations. CS 4620 Lecture Kavita Bala w/ prior instructor Steve Marschner. Cornell CS4620 Fall 2015 Lecture 11 3D Transformations CS 4620 Lecture 11 1 Announcements A2 due tomorrow Demos on Monday Please sign up for a slot Post on piazza 2 Translation 3 Scaling 4 Rotation about z axis 5 Rotation about x axis 6

More information

Perspective projection and Transformations

Perspective projection and Transformations Perspective projection and Transformations The pinhole camera The pinhole camera P = (X,,) p = (x,y) O λ = 0 Q λ = O λ = 1 Q λ = P =-1 Q λ X = 0 + λ X 0, 0 + λ 0, 0 + λ 0 = (λx, λ, λ) The pinhole camera

More information

Quaternions & Rotation in 3D Space

Quaternions & Rotation in 3D Space Quaternions & Rotation in 3D Space 1 Overview Quaternions: definition Quaternion properties Quaternions and rotation matrices Quaternion-rotation matrices relationship Spherical linear interpolation Concluding

More information

2D Transformations. Why Transformations. Translation 4/17/2009

2D Transformations. Why Transformations. Translation 4/17/2009 4/7/9 D Tansfomations Wh Tansfomations Coodinate sstem tansfomations Placing objects in the wold Move/animate the camea fo navigation Dawing hieachical chaactes Animation Tanslation + d 5,4 + d,3 d 4,

More information

Quaternions and Euler Angles

Quaternions and Euler Angles Quaternions and Euler Angles Revision #1 This document describes how the VR Audio Kit handles the orientation of the 3D Sound One headset using quaternions and Euler angles, and how to convert between

More information

CS-184: Computer Graphics. Today. Lecture #5: 3D Transformations and Rotations. Transformations in 3D Rotations

CS-184: Computer Graphics. Today. Lecture #5: 3D Transformations and Rotations. Transformations in 3D Rotations CS-184: Compute Gaphics Lectue #5: 3D Tansfomations and Rotations Pof. James O Bien Univesity of Califonia, Bekeley V2009-F-05-1.0 Today Tansfomations in 3D Rotations Matices Eule angles Eponential maps

More information

Transforms II. Overview. Homogeneous Coordinates 3-D Transforms Viewing Projections. Homogeneous Coordinates. x y z w

Transforms II. Overview. Homogeneous Coordinates 3-D Transforms Viewing Projections. Homogeneous Coordinates. x y z w Transforms II Overvie Homogeneous Coordinates 3- Transforms Vieing Projections 2 Homogeneous Coordinates Allos translations to be included into matri transform. Allos us to distinguish beteen a vector

More information

Extended Perspective Shadow Maps (XPSM) Vladislav Gusev, ,

Extended Perspective Shadow Maps (XPSM)   Vladislav Gusev, , Extended Pespective Shadow Maps (XPSM) http://xpsm.og Vladislav Gusev,.8.27, xmvlad@gmail.com Figue : XPSM esults (~4 objects in a scene, 536x536 shadow map). Intoduction Shadows ae one of the most impotant

More information

2. PROPELLER GEOMETRY

2. PROPELLER GEOMETRY a) Fames of Refeence 2. PROPELLER GEOMETRY 10 th Intenational Towing Tank Committee (ITTC) initiated the pepaation of a dictionay and nomenclatue of ship hydodynamic tems and this wok was completed in

More information

Introduction To Robotics (Kinematics, Dynamics, and Design)

Introduction To Robotics (Kinematics, Dynamics, and Design) Intoduction o obotics Kinematics Dnamics and Design EION # 9: satial Descitions & ansfomations li Meghdai ofesso chool of Mechanical Engineeing haif Univesit of echnolog ehan IN 365-9567 Homeage: htt://meghdai.shaif.edu

More information

Single View Geometry. Camera model & Orientation + Position estimation. What am I?

Single View Geometry. Camera model & Orientation + Position estimation. What am I? Single View Geometry Camera model & Orientation + Position estimation What am I? Vanishing points & line http://www.wetcanvas.com/ http://pennpaint.blogspot.com/ http://www.joshuanava.biz/perspective/in-other-words-the-observer-simply-points-in-thesame-direction-as-the-lines-in-order-to-find-their-vanishing-point.html

More information

Single View Geometry. Camera model & Orientation + Position estimation. What am I?

Single View Geometry. Camera model & Orientation + Position estimation. What am I? Single View Geometr Camera model & Orientation + Position estimation What am I? Ideal case: c Projection equation: x = f X / Z = f Y / Z c p f C x c Zx = f X Z = f Y Z = Z Step 1: Camera projection matrix

More information

ME 210 Applied Mathematics for Mechanical Engineers

ME 210 Applied Mathematics for Mechanical Engineers Note that the unit vectos, T, N and B ae thee unit vectos pependicula to each othe whose diections ae dictated by the local behavio of the cuve C at its point P. They fom a moving ight handed vecto fame

More information

Control of Mobile Robots

Control of Mobile Robots Conto of Mobie obots efeences: -. Siegwat and I.. Noubakhsh, Intoduction to Autonomous Mobie obots, MIT, 004 (Chaps.,3. - S. G. Tzafestas, Intoduction to Mobie obot Conto, Esevie, 013. 1 Tpes of Mobie

More information

fmri pre-processing Juergen Dukart

fmri pre-processing Juergen Dukart fmri pre-processing Juergen Dukart Outline Why do we need pre-processing? fmri pre-processing Slice time correction Realignment Unwarping Coregistration Spatial normalisation Smoothing Overview fmri time-series

More information

Geometric Transformations

Geometric Transformations Geometric Transformations CS 4620 Lecture 9 2017 Steve Marschner 1 A little quick math background Notation for sets, functions, mappings Linear and affine transformations Matrices Matrix-vector multiplication

More information

ANNOUNCEMENT. LECTURE 25 Spherical Refracting Surfaces

ANNOUNCEMENT. LECTURE 25 Spherical Refracting Surfaces ANNUNCEMENT Final: Thusday Dec 3, 208, 7 PM - 9 PM Location: Elliot Hall of Music Coves all eadings, lectues, homewok fom Chaptes 28 though 33 Multiple choice Pactice exams n the couse website and on CHIP

More information

9.5 Polar Coordinates. Copyright Cengage Learning. All rights reserved.

9.5 Polar Coordinates. Copyright Cengage Learning. All rights reserved. 9.5 Polar Coordinates Copyright Cengage Learning. All rights reserved. Introduction Representation of graphs of equations as collections of points (x, y), where x and y represent the directed distances

More information

Sphero Lightning Lab Cheat Sheet

Sphero Lightning Lab Cheat Sheet Actions Tool Description Variables Ranges Roll Combines heading, speed and time variables to make the robot roll. Duration Speed Heading (0 to 999999 seconds) (degrees 0-359) Set Speed Sets the speed of

More information

Single View Geometry. Camera model & Orientation + Position estimation. Jianbo Shi. What am I? University of Pennsylvania GRASP

Single View Geometry. Camera model & Orientation + Position estimation. Jianbo Shi. What am I? University of Pennsylvania GRASP Single View Geometry Camera model & Orientation + Position estimation Jianbo Shi What am I? 1 Camera projection model The overall goal is to compute 3D geometry of the scene from just 2D images. We will

More information

CSE 165: 3D User Interaction

CSE 165: 3D User Interaction CSE 165: 3D Use Inteaction Lectue #6: Selection Instucto: Jugen Schulze, Ph.D. 2 Announcements Homewok Assignment #2 Due Fiday, Januay 23 d at 1:00pm 3 4 Selection and Manipulation 5 Why ae Selection and

More information

Computer Graphics: Viewing in 3-D. Course Website:

Computer Graphics: Viewing in 3-D. Course Website: Computer Graphics: Viewing in 3-D Course Website: http://www.comp.dit.ie/bmacnamee 2 Contents Transformations in 3-D How do transformations in 3-D work? 3-D homogeneous coordinates and matrix based transformations

More information

This group contain tools that are no longer so required, but could still prove useful in the right circumstances.

This group contain tools that are no longer so required, but could still prove useful in the right circumstances. Rotate - More This group contain tools that are no longer so required, but could still prove useful in the right circumstances. Dangle Vortex Tool Vortex Applied Rotate to Axis Rotate Any Axis How to use

More information

Polar Coordinates. Chapter 10: Parametric Equations and Polar coordinates, Section 10.3: Polar coordinates 27 / 45

Polar Coordinates. Chapter 10: Parametric Equations and Polar coordinates, Section 10.3: Polar coordinates 27 / 45 : Given any point P = (x, y) on the plane r stands for the distance from the origin (0, 0). θ stands for the angle from positive x-axis to OP. Polar coordinate: (r, θ) Chapter 10: Parametric Equations

More information

Visualisation Pipeline : The Virtual Camera

Visualisation Pipeline : The Virtual Camera Visualisation Pipeline : The Virtual Camera The Graphics Pipeline 3D Pipeline The Virtual Camera The Camera is defined by using a parallelepiped as a view volume with two of the walls used as the near

More information

Goal. Rendering Complex Scenes on Mobile Terminals or on the web. Rendering on Mobile Terminals. Rendering on Mobile Terminals. Walking through images

Goal. Rendering Complex Scenes on Mobile Terminals or on the web. Rendering on Mobile Terminals. Rendering on Mobile Terminals. Walking through images Goal Walking though s -------------------------------------------- Kadi Bouatouch IRISA Univesité de Rennes I, Fance Rendeing Comple Scenes on Mobile Teminals o on the web Rendeing on Mobile Teminals Rendeing

More information

6.7. POLAR COORDINATES

6.7. POLAR COORDINATES 6.7. POLAR COORDINATES What You Should Learn Plot points on the polar coordinate system. Convert points from rectangular to polar form and vice versa. Convert equations from rectangular to polar form and

More information

Lecture 5: Transforms II. Computer Graphics and Imaging UC Berkeley CS184/284A

Lecture 5: Transforms II. Computer Graphics and Imaging UC Berkeley CS184/284A Lecture 5: Transforms II Computer Graphics and Imaging UC Berkeley 3D Transforms 3D Transformations Use homogeneous coordinates again: 3D point = (x, y, z, 1) T 3D vector = (x, y, z, 0) T Use 4 4 matrices

More information

Local Coordinate Systems From Motion Capture Data

Local Coordinate Systems From Motion Capture Data Local Coordinate Systems From Motion Capture Data Anatomical Coordinate Systems (thigh) How to calculate the anatomical coordinate systems 1) Find the Hip center 2) Find the Knee center 3) Find the Inferior/Superior

More information

Camera Registration in a 3D City Model. Min Ding CS294-6 Final Presentation Dec 13, 2006

Camera Registration in a 3D City Model. Min Ding CS294-6 Final Presentation Dec 13, 2006 Camera Registration in a 3D City Model Min Ding CS294-6 Final Presentation Dec 13, 2006 Goal: Reconstruct 3D city model usable for virtual walk- and fly-throughs Virtual reality Urban planning Simulation

More information

Modeling Transformations

Modeling Transformations Modeling Transformations Michael Kazhdan (601.457/657) HB Ch. 5 FvDFH Ch. 5 Announcement Assignment 2 has been posted: Due: 10/24 ASAP: Download the code and make sure it compiles» On windows: just build

More information

All lengths in meters. E = = 7800 kg/m 3

All lengths in meters. E = = 7800 kg/m 3 Poblem desciption In this poblem, we apply the component mode synthesis (CMS) technique to a simple beam model. 2 0.02 0.02 All lengths in metes. E = 2.07 10 11 N/m 2 = 7800 kg/m 3 The beam is a fee-fee

More information

3D Shape Reconstruction (from Photos)

3D Shape Reconstruction (from Photos) 3D Shape Reconstuction (fo Photos) CS434 Daniel G. Aliaga Depatent of Copute Science Pudue Univesity Thanks to S. Naasihan @ CMU fo soe of the slides Poble Stateent How to ceate (ealistic) 3D odels of

More information

MEAM 620: HW 1. Sachin Chitta Assigned: January 10, 2007 Due: January 22, January 10, 2007

MEAM 620: HW 1. Sachin Chitta Assigned: January 10, 2007 Due: January 22, January 10, 2007 MEAM 620: HW 1 Sachin Chitta (sachinc@grasp.upenn.edu) Assigned: January 10, 2007 Due: January 22, 2006 January 10, 2007 1: MATLAB Programming assignment Using MATLAB, write the following functions: 1.

More information

Single View Geometry. Camera model & Orientation + Position estimation. What am I?

Single View Geometry. Camera model & Orientation + Position estimation. What am I? Single View Geometry Camera model & Orientation + Position estimation What am I? Vanishing point Mapping from 3D to 2D Point & Line Goal: Point Homogeneous coordinates represent coordinates in 2 dimensions

More information

CIS 580, Machine Perception, Spring 2016 Homework 2 Due: :59AM

CIS 580, Machine Perception, Spring 2016 Homework 2 Due: :59AM CIS 580, Machine Perception, Spring 2016 Homework 2 Due: 2015.02.24. 11:59AM Instructions. Submit your answers in PDF form to Canvas. This is an individual assignment. 1 Recover camera orientation By observing

More information

Geometric transformations in 3D and coordinate frames. Computer Graphics CSE 167 Lecture 3

Geometric transformations in 3D and coordinate frames. Computer Graphics CSE 167 Lecture 3 Geometric transformations in 3D and coordinate frames Computer Graphics CSE 167 Lecture 3 CSE 167: Computer Graphics 3D points as vectors Geometric transformations in 3D Coordinate frames CSE 167, Winter

More information

METR Robotics Tutorial 2 Week 3: Homogeneous Coordinates SOLUTIONS & COMMENTARY

METR Robotics Tutorial 2 Week 3: Homogeneous Coordinates SOLUTIONS & COMMENTARY METR4202 -- Robotics Tutorial 2 Week 3: Homogeneous Coordinates SOLUTIONS & COMMENTARY Questions 1. Calculate the homogeneous transformation matrix A BT given the [20 points] translations ( A P B ) and

More information

9/5/2018. Physics colloquium today -- 9/05/2018 PHY 711 Fall Lecture /05/2018 PHY 711 Fall Lecture 4 3

9/5/2018. Physics colloquium today -- 9/05/2018 PHY 711 Fall Lecture /05/2018 PHY 711 Fall Lecture 4 3 PHY 7 Classical Mechanics and Mathematical Methods 0-0:50 AM MWF Olin 03 Plan fo Lectue 4: Reading: Chapte F&W. Summay of pevious discussion of scatteing theoy; tansfomation etween la and cente of mass

More information

GOSAT TANSO-FTS Polarization Model Description

GOSAT TANSO-FTS Polarization Model Description GO TANO-FT Polaization odel Descition June, Contact: kuze.akihiko@jaxa.j Refeence Kuze et al.,al. Otics, 48,, 676 6733 (9). TANO-FT Otics cene flux fom nadi Dee sace view Black body view Diffused sola

More information

Inertial Measurement Units II!

Inertial Measurement Units II! ! Inertial Measurement Units II! Gordon Wetzstein! Stanford University! EE 267 Virtual Reality! Lecture 10! stanford.edu/class/ee267/!! wikipedia! Polynesian Migration! Lecture Overview! short review of

More information

IB-2 Polarization Practice

IB-2 Polarization Practice Name: 1. Plane-polarized light is incident normally on a polarizer which is able to rotate in the plane perpendicular to the light as shown below. In diagram 1, the intensity of the incident light is 8

More information

Perspective Projection Describes Image Formation Berthold K.P. Horn

Perspective Projection Describes Image Formation Berthold K.P. Horn Perspective Projection Describes Image Formation Berthold K.P. Horn Wheel Alignment: Camber, Caster, Toe-In, SAI, Camber: angle between axle and horizontal plane. Toe: angle between projection of axle

More information

Modeling Transformations

Modeling Transformations Modeling Transformations Michael Kazhdan (601.457/657) HB Ch. 5 FvDFH Ch. 5 Overview Ra-Tracing so far Modeling transformations Ra Tracing Image RaTrace(Camera camera, Scene scene, int width, int heigh,

More information

Mono Vision Based Construction of Elevation Maps in Indoor Environments

Mono Vision Based Construction of Elevation Maps in Indoor Environments 8th WSEAS Intenational onfeence on SIGNAL PROESSING, OMPUTATIONAL GEOMETRY and ARTIFIIAL VISION (ISGAV 08) Rhodes, Geece, August 0-, 008 Mono Vision Based onstuction of Elevation Maps in Indoo Envionments

More information

Shape Matching / Object Recognition

Shape Matching / Object Recognition Image Pocessing - Lesson 4 Poduction Line object classification Object Recognition Shape Repesentation Coelation Methods Nomalized Coelation Local Methods Featue Matching Coespondence Poblem Alignment

More information

Curl, Divergence, and Gradient in Cylindrical and Spherical Coordinate Systems

Curl, Divergence, and Gradient in Cylindrical and Spherical Coordinate Systems APPENDIX B Cul, Divegence, and Gadient in Cylindical and Spheical Coodinate Systems In Sections 3., 3.4, and 6., we intoduced the cul, divegence, and gadient, espectively, and deived the expessions o them

More information

9-2. Camera Calibration Method for Far Range Stereovision Sensors Used in Vehicles. Tiberiu Marita, Florin Oniga, Sergiu Nedevschi

9-2. Camera Calibration Method for Far Range Stereovision Sensors Used in Vehicles. Tiberiu Marita, Florin Oniga, Sergiu Nedevschi 9-2 Camea Calibation Method fo Fa Range Steeovision Sensos Used in Vehicles ibeiu Maita, Floin Oniga, Segiu Nedevschi Compute Science Depatment echnical Univesity of Cluj-Napoca Cluj-Napoca, 400020, ROMNI

More information

You will be writing code in the Python programming language, which you may have learnt in the Python module.

You will be writing code in the Python programming language, which you may have learnt in the Python module. Tightrope Introduction: In this project you will create a game in which you have to tilt your Sense HAT to guide a character along a path. If you fall off the path, you have to start again from the beginning!

More information

Collision Detection with Swept Spheres and Ellipsoids

Collision Detection with Swept Spheres and Ellipsoids Collision etection with Swet Shees and Ellisoids Joit Rouwé joit@games.lostbos.com Souce code: htt://www.thee4.demon.nl/swetellisoid/swetellisoid.zi. Intoduction Toda most games use conex olgons fo collision

More information

NEW FINITE ELEMENT / MULTIBODY SYSTEM ALGORITHM FOR MODELING FLEXIBLE TRACKED VEHICLES

NEW FINITE ELEMENT / MULTIBODY SYSTEM ALGORITHM FOR MODELING FLEXIBLE TRACKED VEHICLES 2011 NDIA GROUND VEHICLE SYSEMS ENGINEERING AND ECHNOLOGY SYMPOSIUM MODELING & SIMULAION, ESING AND VALIDAION (MSV) MINI-SYMPOSIUM AUGUS 9-11 DEARBORN, MICHIGAN NEW FINIE ELEMEN / MULIBODY SYSEM ALGORIHM

More information

Announcements. Equation of Perspective Projection. Image Formation and Cameras

Announcements. Equation of Perspective Projection. Image Formation and Cameras Announcements Image ormation and Cameras Introduction to Computer Vision CSE 52 Lecture 4 Read Trucco & Verri: pp. 22-4 Irfanview: http://www.irfanview.com/ is a good Windows utilit for manipulating images.

More information

Attitude Representation

Attitude Representation Attitude Representation Basilio Bona DAUIN Politecnico di Torino Semester 1, 015-16 B. Bona (DAUIN) Attitude Representation Semester 1, 015-16 1 / 3 Mathematical preliminaries A 3D rotation matrix R =

More information

Lecture 5: Rendering Equation Chapter 2 in Advanced GI

Lecture 5: Rendering Equation Chapter 2 in Advanced GI Lectue 5: Rendeing Equation Chapte in Advanced GI Fall 004 Kavita Bala Compute Science Conell Univesity Radiomety Radiomety: measuement of light enegy Defines elation between Powe Enegy Radiance Radiosity

More information

3-D D Euclidean Space - Vectors

3-D D Euclidean Space - Vectors 3-D D Euclidean Space - Vectors Rigid Body Motion and Image Formation A free vector is defined by a pair of points : Jana Kosecka http://cs.gmu.edu/~kosecka/cs682.html Coordinates of the vector : 3D Rotation

More information

Stereo and 3D Reconstruction

Stereo and 3D Reconstruction Steeo and 3D Reconstuction CS635 Sping 2017 Daniel G. Aliaga Depatent of Copute Science Pudue Univesity Thanks to S. Naasihan @ CMU fo soe of the slides Poble Stateent How to ceate (ealistic) 3D odels

More information

Quaternions and Rotations

Quaternions and Rotations CSCI 520 Computer Animation and Simulation Quaternions and Rotations Jernej Barbic University of Southern California 1 Rotations Very important in computer animation and robotics Joint angles, rigid body

More information

Transformations Review

Transformations Review Transformations Review 1. Plot the original figure then graph the image of Rotate 90 counterclockwise about the origin. 2. Plot the original figure then graph the image of Translate 3 units left and 4

More information

Adaptation of Motion Capture Data of Human Arms to a Humanoid Robot Using Optimization

Adaptation of Motion Capture Data of Human Arms to a Humanoid Robot Using Optimization ICCAS25 June 2-5, KINTEX, Gyeonggi-Do, Koea Adaptation of Motion Captue Data of Human Ams to a Humanoid Robot Using Optimization ChangHwan Kim and Doik Kim Intelligent Robotics Reseach Cente, Koea Institute

More information

Announcements. The equation of projection. Image Formation and Cameras

Announcements. The equation of projection. Image Formation and Cameras Announcements Image ormation and Cameras Introduction to Computer Vision CSE 52 Lecture 4 Read Trucco & Verri: pp. 5-4 HW will be on web site tomorrow or Saturda. Irfanview: http://www.irfanview.com/ is

More information

Augmented Reality. Integrating Computer Graphics with Computer Vision Mihran Tuceryan. August 16, 1998 ICPR 98 1

Augmented Reality. Integrating Computer Graphics with Computer Vision Mihran Tuceryan. August 16, 1998 ICPR 98 1 Augmented Reality Integating Compute Gaphics with Compute Vision Mihan Tuceyan August 6, 998 ICPR 98 Definition XCombines eal and vitual wolds and objects XIt is inteactive and eal-time XThe inteaction

More information

BGC gimbal & Pixhawk SToRM32 Gimbal Controller

BGC gimbal & Pixhawk SToRM32 Gimbal Controller BGC gimbal & Pixhawk SToRM32 Gimbal Controller The SToRM32-BGC is a relatively low-cost 3-axis brushless gimbal controller that can communicate with ArduPilot (Copter, Plane and Rover) using MAVLink. With

More information

Polar Coordinates. Chapter 10: Parametric Equations and Polar coordinates, Section 10.3: Polar coordinates 28 / 46

Polar Coordinates. Chapter 10: Parametric Equations and Polar coordinates, Section 10.3: Polar coordinates 28 / 46 Polar Coordinates Polar Coordinates: Given any point P = (x, y) on the plane r stands for the distance from the origin (0, 0). θ stands for the angle from positive x-axis to OP. Polar coordinate: (r, θ)

More information

= dv 3V (r + a 1) 3 r 3 f(r) = 1. = ( (r + r 2

= dv 3V (r + a 1) 3 r 3 f(r) = 1. = ( (r + r 2 Random Waypoint Model in n-dimensional Space Esa Hyytiä and Joma Vitamo Netwoking Laboatoy, Helsinki Univesity of Technology, Finland Abstact The andom waypoint model (RWP) is one of the most widely used

More information

So we have been talking about 3D viewing, the transformations pertaining to 3D viewing. Today we will continue on it. (Refer Slide Time: 1:15)

So we have been talking about 3D viewing, the transformations pertaining to 3D viewing. Today we will continue on it. (Refer Slide Time: 1:15) Introduction to Computer Graphics Dr. Prem Kalra Department of Computer Science and Engineering Indian Institute of Technology, Delhi Lecture - 8 3D Viewing So we have been talking about 3D viewing, the

More information

Camera Model and Calibration

Camera Model and Calibration Camera Model and Calibration Lecture-10 Camera Calibration Determine extrinsic and intrinsic parameters of camera Extrinsic 3D location and orientation of camera Intrinsic Focal length The size of the

More information

Unit 13: Periodic Functions and Trig

Unit 13: Periodic Functions and Trig Date Period Unit 13: Periodic Functions and Trig Day Topic 0 Special Right Triangles and Periodic Function 1 Special Right Triangles Standard Position Coterminal Angles 2 Unit Circle Cosine & Sine (x,

More information

CS 450: COMPUTER GRAPHICS QUATERNIONS SPRING 2016 DR. MICHAEL J. REALE

CS 450: COMPUTER GRAPHICS QUATERNIONS SPRING 2016 DR. MICHAEL J. REALE CS 45: COMPUTER GRAPHICS QUATERNIONS SPRING 6 DR. MICHAEL J. REALE http://common.ikimedia.og/iki/fi le%3awilliam_roan_hamilton_pot ait_oal_combined.png INTRODUCTION Quatenion inented b Si William Roan

More information

Machine learning based automatic extrinsic calibration of an onboard monocular camera for driving assistance applications on smart mobile devices

Machine learning based automatic extrinsic calibration of an onboard monocular camera for driving assistance applications on smart mobile devices Technical University of Cluj-Napoca Image Processing and Pattern Recognition Research Center www.cv.utcluj.ro Machine learning based automatic extrinsic calibration of an onboard monocular camera for driving

More information

Curves from the inside

Curves from the inside MATH 2411 - Harrell Curves from the inside Lecture 4 Copyright 2013 by Evans M. Harrell II. Example: tangent line to a spiral If your careening car smashes into another, how can you calculate the angle

More information

CHAPTER 40 CARTESIAN AND POLAR COORDINATES

CHAPTER 40 CARTESIAN AND POLAR COORDINATES CHAPTER 40 CARTESIAN AND POLAR COORDINATES EXERCISE 169 Page 462 1. Express (3, 5) as polar coordinates, correct to 2 decimal places, in both degrees and in From the diagram, r = 32 + 52 = 5.83 y and 5

More information

17/5/2009. Introduction

17/5/2009. Introduction 7/5/9 Steeo Imaging Intoduction Eample of Human Vision Peception of Depth fom Left and ight eye images Diffeence in elative position of object in left and ight eyes. Depth infomation in the views?? 7/5/9

More information

Autonomous Navigation for Flying Robots

Autonomous Navigation for Flying Robots Computer Vision Group Prof. Daniel Cremers Autonomous Navigation for Flying Robots Lecture 3.1: 3D Geometry Jürgen Sturm Technische Universität München Points in 3D 3D point Augmented vector Homogeneous

More information

Tracker Software. 103 年 11 月 Department of Physics, NDHU 國立東華大學物理學系製作

Tracker Software. 103 年 11 月 Department of Physics, NDHU 國立東華大學物理學系製作 Tracker Software 103 年 11 月 Department of Physics, NDHU Tracker Software 1. Tracker s main user interface 1.1. Choose Language 編輯 (Edit) 語言 (Language) English 2. Open the files File Open File Video Open

More information

CHAPTER 2 SENSOR DATA SIMULATION: A KINEMATIC APPROACH

CHAPTER 2 SENSOR DATA SIMULATION: A KINEMATIC APPROACH 27 CHAPTER 2 SENSOR DATA SIMULATION: A KINEMATIC APPROACH 2.1 INTRODUCTION The standard technique of generating sensor data for navigation is the dynamic approach. As revealed in the literature (John Blakelock

More information

CS184: Using Quaternions to Represent Rotation

CS184: Using Quaternions to Represent Rotation Page 1 of 5 CS 184 home page A note on these notes: These notes on quaternions were created as a resource for students taking CS184 at UC Berkeley. I am not doing any research related to quaternions and

More information

To graph the point (r, θ), simply go out r units along the initial ray, then rotate through the angle θ. The point (1, 5π 6

To graph the point (r, θ), simply go out r units along the initial ray, then rotate through the angle θ. The point (1, 5π 6 Polar Coordinates Any point in the plane can be described by the Cartesian coordinates (x, y), where x and y are measured along the corresponding axes. However, this is not the only way to represent points

More information

A Robust Docking Strategy for a Mobile Robot using Flow Field Divergence

A Robust Docking Strategy for a Mobile Robot using Flow Field Divergence A Robust Docking Stateg fo a Mobile Robot using Flow Field Divegence Chis McCath and Nick Banes Vision Science, Technolog and Applications Pogamme National ICT Austalia Canbea, Austalia. cdmcc@sise.anu.edu.au

More information

3D Viewing Transformations

3D Viewing Transformations 3D Viewing Transformations Eric C. McCreath School of Computer Science The Australian National University ACT 2 Australia ericm@cs.anu.edu.au Overview 2 3D Matri Transformations Model/World/Viewing/Project/Viewport

More information

ECE 634: Digital Video Systems Mo7on models: 1/19/17

ECE 634: Digital Video Systems Mo7on models: 1/19/17 ECE 634: Digital Video Systems Mo7on models: 1/19/17 Professor Amy Reibman MSEE 356 reibman@purdue.edu hip://engineering.purdue.edu/~reibman/ece634/index.html Outline Today: Mo7on models for mo7on es7ma7on

More information

Camera Parameters Estimation from Hand-labelled Sun Sositions in Image Sequences

Camera Parameters Estimation from Hand-labelled Sun Sositions in Image Sequences Camera Parameters Estimation from Hand-labelled Sun Sositions in Image Sequences Jean-François Lalonde, Srinivasa G. Narasimhan and Alexei A. Efros {jlalonde,srinivas,efros}@cs.cmu.edu CMU-RI-TR-8-32 July

More information

Computer Graphics. - Shading - Hendrik Lensch. Computer Graphics WS07/08 Light Transport

Computer Graphics. - Shading - Hendrik Lensch. Computer Graphics WS07/08 Light Transport Compute Gaphics - Shading - Hendik Lensch Compute Gaphics WS07/08 Light Tanspot Oveview So fa Nuts and bolts of ay tacing Today Reflectance Reflection models Compute Gaphics WS07/08 Light Tanspot Mateial

More information

Computing tilt measurement and tilt-compensated e-compass

Computing tilt measurement and tilt-compensated e-compass DT0058 Design tip Computing tilt measurement and tilt-compensated e-compass By Andrea Vitali Main components LSM303AGR LSM303C LSM303D Ultra compact high-performance e-compass: ultra-low-power 3D accelerometer

More information

CS 548: COMPUTER GRAPHICS QUATERNIONS SPRING 2015 DR. MICHAEL J. REALE

CS 548: COMPUTER GRAPHICS QUATERNIONS SPRING 2015 DR. MICHAEL J. REALE CS 548: COMPUTER GRAPHICS QUATERNIONS SPRING 5 DR. MICHAEL J. REALE http://common.ikimedia.og/iki/fi le%3awilliam_roan_hamilton_pot ait_oal_combined.png INTRODUCTION Quatenion inented b Si William Roan

More information

The Importance of Matrices in the DirectX API. by adding support in the programming language for frequently used calculations.

The Importance of Matrices in the DirectX API. by adding support in the programming language for frequently used calculations. Hermann Chong Dr. King Linear Algebra Applications 28 November 2001 The Importance of Matrices in the DirectX API In the world of 3D gaming, there are two APIs (Application Program Interface) that reign

More information

Color Correction Using 3D Multiview Geometry

Color Correction Using 3D Multiview Geometry Colo Coection Using 3D Multiview Geomety Dong-Won Shin and Yo-Sung Ho Gwangju Institute of Science and Technology (GIST) 13 Cheomdan-gwagio, Buk-ku, Gwangju 500-71, Republic of Koea ABSTRACT Recently,

More information

Topography Reconstruction by Interferometric SAR Look Vector's Orthogonal Decomposition

Topography Reconstruction by Interferometric SAR Look Vector's Orthogonal Decomposition 005 WSEAS Int. Conf. on REMOTE SENSING, Venice, Italy, Novembe -4, 005 (pp89-94) Topogaphy Reconstuction by Intefeometic SAR Look Vecto's Othogonal Decomposition S. REDADAA 1 and M. BENSLAMA 1 Laboatoy

More information

Lecture 3.5: Sumary of Inverse Kinematics Solutions

Lecture 3.5: Sumary of Inverse Kinematics Solutions MCE/EEC 647/747: Robot Dynamics and Control Lecture 3.5: Sumary of Inverse Kinematics Solutions Reading: SHV Sect.2.5.1, 3.3 Mechanical Engineering Hanz Richter, PhD MCE647 p.1/13 Inverse Orientation:

More information

Vision Review: Image Formation. Course web page:

Vision Review: Image Formation. Course web page: Vision Review: Image Formation Course web page: www.cis.udel.edu/~cer/arv September 10, 2002 Announcements Lecture on Thursday will be about Matlab; next Tuesday will be Image Processing The dates some

More information

521466S Machine Vision Exercise #1 Camera models

521466S Machine Vision Exercise #1 Camera models 52466S Machine Vision Exercise # Camera models. Pinhole camera. The perspective projection equations or a pinhole camera are x n = x c, = y c, where x n = [x n, ] are the normalized image coordinates,

More information

Environment Mapping. Overview

Environment Mapping. Overview Envionment Mapping 1 Oveview Intoduction Envionment map constuction sphee mapping Envionment mapping applications distant geomety eflections 2 1 Oveview Intoduction Envionment map constuction sphee mapping

More information