Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Office 432 Carver Phone 515-294-8141

Slides:



Advertisements
Similar presentations
Announcements. Structure-from-Motion Determining the 3-D structure of the world, and/or the motion of a camera using a sequence of images taken by a moving.
Advertisements

Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone
COMPUTER GRAPHICS 2D TRANSFORMATIONS.
Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Office 432 Carver Phone
General Physics (PHYS101)
Geometry (Many slides adapted from Octavia Camps and Amitabh Varshney)
Linear Algebra and SVD (Some slides adapted from Octavia Camps)
CS 376 Introduction to Computer Graphics 02 / 09 / 2007 Instructor: Michael Eckmann.
Computer Graphics CSC 630 Lecture 2- Linear Algebra.
4.4 Transformations with Matrices
Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone
Instructor: Irvin Roy Hentzel Office 432 Carver Phone
Chapter one Linear Equations
Mathematical Fundamentals
COS 397 Computer Graphics Svetla Boytcheva AUBG, Spring 2013.
2.2 Linear Transformations in Geometry For an animation of this topic visit
Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone
January 22 Inverse of Matrices. Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver.
Key Ideas.  A quantity is a an exact amount or measurement.  A quantity can be exact or approximate depending on the level of accuracy required.
Geometric Transformation. So far…. We have been discussing the basic elements of geometric programming. We have discussed points, vectors and their operations.
Elementary Linear Algebra Anton & Rorres, 9th Edition
Dx = 2 dy = 3 Y X D Translation A translation is applied to an object by repositioning it along a straight-line path.
2D Geometric Transformations
6.837 Linear Algebra Review Patrick Nichols Thursday, September 18, 2003.
Graphing Techniques: Transformations
1 MAC 2103 Module 6 Euclidean Vector Spaces I. 2 Rev.F09 Learning Objectives Upon completing this module, you should be able to: 1. Use vector notation.
CO1301: Games Concepts Dr Nick Mitchell (Room CM 226) Material originally prepared by Gareth Bellaby.
CS 325 Introduction to Computer Graphics 02 / 17 / 2010 Instructor: Michael Eckmann.
January 22 Review questions. Math 307 Spring 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone.
Chapter 7 Transformations.
Warm Up 1. Reflect the preimage using y=x as the line of reflection given the following coordinates: A(-2, 4), B(-4, -2), C(-5, 6) 2. Rotate the figure.
CS 376 Introduction to Computer Graphics 02 / 16 / 2007 Instructor: Michael Eckmann.
Page 146 Chapter 3 True False Questions. 1. The image of a 3x4 matrix is a subspace of R 4 ? False. It is a subspace of R 3.
Chap. 6 Linear Transformations
Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone
Matrices A matrix is a table or array of numbers arranged in rows and columns The order of a matrix is given by stating its dimensions. This is known as.
Advanced Algebra II Notes 4.5 Reflections and the Square Root Family
Chapter 4 Linear Transformations 4.1 Introduction to Linear Transformations 4.2 The Kernel and Range of a Linear Transformation 4.3 Matrices for Linear.
Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone
Transformation in Geometry Transformation A transformation changes the position or size of a shape on a coordinate plane.
Transformations A rule for moving every point in a figure to a new location.
Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone
Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone
CO1301: Games Concepts Dr Nick Mitchell (Room CM 226) Material originally prepared by Gareth Bellaby.
Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone
Computer Graphics 3D Transformations. Translation.
Objective: Students will be able to represent translations, dilations, reflections and rotations with matrices.
3D Transformation A 3D point (x,y,z) – x,y, and z coordinates
3-D Geometric Transformations
3D Geometric Transformation
A function is a rule f that associates with each element in a set A one and only one element in a set B. If f associates the element b with the element.
9.3 – Perform Reflections. Reflection: Transformation that uses a line like a mirror to reflect an image Line of Reflection: Mirror line in a reflection.
Jinxiang Chai CSCE441: Computer Graphics 3D Transformations 0.
Chapter 9 Properties of Transformations Warren Luo Matthew Yom.
CS 376 Introduction to Computer Graphics 02 / 14 / 2007 Instructor: Michael Eckmann.
Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone
CS 551 / 645: Introductory Computer Graphics Viewing Transforms.
CS 325 Introduction to Computer Graphics 02 / 19 / 2010 Instructor: Michael Eckmann.
Computer Graphics Mathematical Fundamentals Lecture 10 Taqdees A. Siddiqi
Computer Graphics Lecture 11 2D Transformations I Taqdees A. Siddiqi
Geometric Transformations Ceng 477 Introduction to Computer Graphics Computer Engineering METU.
Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Instructor: Irvin Roy Hentzel Office 432 Carver Phone
Chapter 4 Linear Transformations 4.1 Introduction to Linear Transformations 4.2 The Kernel and Range of a Linear Transformation 4.3 Matrices for Linear.
Robotic Arms and Matrices By Chris Wong and Chris Marino.
Transformation in Geometry Transformation A transformation changes the position or size of a polygon on a coordinate plane.
3D Geometric Transformation
Computer Graphics CC416 Week 15 3D Graphics.
Instructor: Irvin Roy Hentzel Office 432 Carver Phone
Linear Algebra A gentle introduction
Chapter 4 Linear Transformations
Presentation transcript:

Math 307 Spring, 2003 Hentzel Time: 1:10-2:00 MWF Room: 1324 Howe Hall Office 432 Carver Phone Text: Linear Algebra With Applications, Second Edition Otto Bretscher

Wednesday, Jan 29, Chapter 2.2 Page 61 Problems 2,18,44 Main Idea: Matrices can stretch things out and twist them around. Key Words: Rotation, Dilation, Linear Transformation Goal: Look at a matrix and visualize what it does.

Previous Assignment: Page 48 Problems 32,34,42 Page 48 Problem 32: Find an nxn matrix A such that AX = 3 X for all X in R n. ans: A = 3 I.

Page 48 Problem 34: Consider the transformation T from R 2 to R 2 that rotates any vector X through a given angle t in the counterclockwise direction. Find the matrix of T in terms of t. ans: A = | Cos[t] -Sin[t] | | Sin[t] Cos[t] |.

Page 48 Problem 42: When you represent a three-dimensional object graphically in the plane (on paper, the blackboard, or a computer screen), you have to transform spatial coordinates | x1 | | x2 | into plane coordinates | y1 |. | x3 | | y2 | The simplest choice is a linear transformation, for example, the one given by the matrix | -1/2 1 0 | | -1/2 0 1 |.

(a) Use this transformation to represent the unit cube with corner points | | | | | | Include the images of the x1, x2, x3 axes in your sketch. | -1/2 1 0 | | | | -1/2 0 1 | | | = | | | 0 -1/ /2 1 -1/2 1/2 | | 0 -1/ /2 1 1/2 1/2 |

New Material: Definition: A linear transformation does just what any reasonable person would expect. These are (a) T(V+W) = T(V)+T(W) for all vectors V,W. (b) T(cV) = c T(V) for all numbers c and all vectors V.

If you buy three bags of groceries, the cost of these three bags all together is the same as adding the cost of all three bags separately. Cost[ B 1 +B 2 +B 3 ] = Cost[B 1 ]+Cost[B 2 ]+Cost[B 3 ] The cost of three identical bags of groceries is three times the cost of one of the bags. Cost[3 B] = 3 Cost[ B ].

Now you can argue that if you buy in quantities, then you can get things cheaper. Fine! Then the cost is not a linear function. Most processes are linear if the changes are not too large. For example: If you want to produce 10% more cars, you need 10% more labor and 10% more material.

In J.I.Case Company in Burlington, they made three models of crawler tractors, the 310, the 750, and the Their computer had a list of 20,000 parts which were in the inventory. Whenever an order came in for a tractor, the computer would subtract the parts needed from the inventory. As one would suspect, the parts function is linear.

If they wanted to make: 3 of the 310, 5 of the 750, 2 of the 1000's, then: Parts(3V V V 1000 ) = 3 Parts(V 310 ) + 5 Parts(V 750 ) + 2 Parts(V 1000 )

The area of matrices limits itself to things which behave linearly. Show that this function is linear. | a | | a+b | T| b | = | b-c |. | c | First: | 2 | | 5 | What is T | 3 | ? ans |-1 |. | 4 | | 1 | | 0 | What is T| -1 | ? ans | 0 |. | -1 |

Part (i): We have to check that T(V+W) = T(V) + T(W) | a | | x | | a+x | T(| b | + | y | ) = T( | b+y | ) | c | | z | | c+z | = |a+x+b+y| = | a+b | + |x+y| |b+y-c-z| | b-c | |y-z| | a | | x | = T( | b | ) + T( | y | ). | c | | z |

Part (ii). We have to show that T(cV) = c T(V). | x | | cx | T( c | y | ) = T( | cy | ) | z | | cz | |x| = |cx+cy| = c |x+y|= c T(|y|). |cy–cz| |y-z| |z|

Any linear function can be represented by a matrix. The matrix for T is gotten by evaluating the situation and writing down just what it has to be. First, Since T converts a vector of length three to a vector of length 2, T must be a 2x3 matrix. | a | | a+b | T| b | = | b - c | | c |

| a | | a + b | T| b | = | b - c | | c | T = | | | | Check it with a general vector as follows | | | a | | a + b | | | | b | = | b - c | | c |

Write the matrix for: | x | | 1x + 2y + z | f| y | = | 2x + 5y - z | | z | | 5x + 4y +24z | Notice that the matrix is just | | 1 | | 0 | | 0 | | | f| 0 | f| 1 | f| 0 | | | | 0 | | 0 | | 1 | | | | = | | | |

(a) Write the matrix for rotation of the x-y plane by 90 degrees. (b) Write the matrix for rotation of the x-y plane by 45 degrees. (c) Write the matrix for rotation of the x-y plane by 30 degrees.

What is the inverse for (a). What is the inverse for (b). What is the inverse for (c).

Rotation Dilation: |1 -1| = Sqrt[2]|1/Sqrt[2] -1/Sqrt[2]| |1 1| |1/Sqrt[2] 1/Sqrt[2]| means it rotates through an angle theta where Cos[theta] = 1/Sqrt[2] and then stretches it by a factor of Sqrt[2].

Shear: There is a line L such that (1) L is left fixed (2) Things not on L are moved parallel to L. i.e. T(v) = v for all v on L. T(v)-v is parallel to L for v not on L.

Show that | 1 1/2 | is a shear. | 0 1 | | a | ----> | a + 1/2 b | | b | | b | For | a | to be fixed, b is zero. | b | Therefore the X-axis is fixed. T| a | - | a | = | 1/2 b | | b | | b | | 0 | Movement is parallel to the X-axis.

Suppose that U and W are perpendicular. That is: U.W = 0. Show that T[X] = X + (U.X) W is a shear parallel to W. T[kW] = kW + (U.kW)W = kW since U.W = 0. T[X]-X = (U.X) W Which is parallel to W.

Projection onto a line in direction U for a Unit vector U. p(X) := (X.U)U. /| X / | / | /-> Line in the direction of U

Reflection in a direction U. X /. / // /./ /. / // U/ f(X) f(X) := 2 (X.U)U - X. f(U) = U If X is perpendicular to U, then X switches sign.

The matrix for a rotation is | Cos[t] -Sin[t] | | Sin[t] Cos[t] | The matrix for a reflection is | Cos[t] Sin[t] | | Sin[t] -Cos[t] | The matrix for a dilation is | c 0 | | 0 c |

Express the linear transformation | 6 8 | as a rotation followed | -8 6 | by a dilation. Notice that the matrix is of the form. 10 | | | | Rotation by ArcSin[-0.8] = degrees followed by a dilation with factor of 10.

Express the linear transformation | 12 5 | | | as a flip followed by a dilation. 13 | 12/13 5/13 | | 5/13 -12/13 | If Cos[theta] = 12/13, this is a flip about the line making the angle 1/2 theta. Then a dilation by the multiple of 13.

How do you tell them apart. | a -b | | a b | | b a | | b -a | rotation reflection You can view the reflection as first doing the rotation and then flipping the new y-axis.