2-D Geometry.

Slides:



Advertisements
Similar presentations
Transformations Ed Angel Professor Emeritus of Computer Science
Advertisements

Computer Graphics Lecture 4 Geometry & Transformations.
Transformations We want to be able to make changes to the image larger/smaller rotate move This can be efficiently achieved through mathematical operations.
Geometric Transformations
2-D Geometry. The Image Formation Pipeline Outline Vector, matrix basics 2-D point transformations Translation, scaling, rotation, shear Homogeneous.
HCI 530 : Seminar (HCI) Damian Schofield. HCI 530: Seminar (HCI) Transforms –Two Dimensional –Three Dimensional The Graphics Pipeline.
1 Geometrical Transformation 2 Outline General Transform 3D Objects Quaternion & 3D Track Ball.
Chapter 4.1 Mathematical Concepts
Chapter 4.1 Mathematical Concepts. 2 Applied Trigonometry Trigonometric functions Defined using right triangle  x y h.
1 CSCE 441 Computer Graphics: 2D Transformations Jinxiang Chai.
CSCE 590E Spring 2007 Basic Math By Jijun Tang. Applied Trigonometry Trigonometric functions  Defined using right triangle  x y h.
Computer Graphics CSC 630 Lecture 2- Linear Algebra.
Computer Vision : CISC4/689
The Image Formation Pipeline
Transformations CS4395: Computer Graphics 1 Mohan Sridharan Based on slides created by Edward Angel.
2D Transformations Unit - 3. Why Transformations? In graphics, once we have an object described, transformations are used to move that object, scale it.
1 Matrix Math ©Anthony Steed Overview n To revise Vectors Matrices n New stuff Homogenous co-ordinates 3D transformations as matrices.
Geometric Intuition Randy Gaul. Vectors, Points and Basis Matrices Rotation Matrices Dot product and how it’s useful Cross product and how it’s useful.
Little Linear Algebra Contents: Linear vector spaces Matrices Special Matrices Matrix & vector Norms.
Geometric Transformation. So far…. We have been discussing the basic elements of geometric programming. We have discussed points, vectors and their operations.
CS 480/680 Computer Graphics Transformations Dr. Frederick C Harris, Jr.
Homogeneous Coordinates (Projective Space) Let be a point in Euclidean space Change to homogeneous coordinates: Defined up to scale: Can go back to non-homogeneous.
2D Geometric Transformations
Matrices, Transformations and the 3D Pipeline Matthew Rusch Paul Keet.
Geometry: 2-D Transformations Course web page: Chapter #3.
Transformations Angel Angel: Interactive Computer Graphics5E © Addison-Wesley
Introduction to Computer Graphics Geometric Transformations
Two-Dimensional Geometric Transformations ch5. 참조 Subjects : Basic Transformations Homogeneous Coordinates Composite Transformations Other Transformations.
1 Graphics CSCI 343, Fall 2015 Lecture 10 Coordinate Transformations.
Computer Graphics Matrices
CSCE 552 Fall 2012 Math By Jijun Tang. Applied Trigonometry Trigonometric functions  Defined using right triangle  x y h.
Honors Geometry.  We learned how to set up a polygon / vertex matrix  We learned how to add matrices  We learned how to multiply matrices.
Computer Graphics I, Fall 2010 Transformations.
1 Angel: Interactive Computer Graphics 4E © Addison-Wesley 2005 Transformations Ed Angel Professor of Computer Science, Electrical and Computer Engineering,
Chapter 4.1 Mathematical Concepts. 2 Applied Trigonometry "Old Henry And His Old Aunt" Defined using right triangle  x y h.
Objectives Introduce standard transformations Introduce standard transformations Derive homogeneous coordinate transformation matrices Derive homogeneous.
CPT450 – Computer Graphics
Computer Graphics 2D Transformations
Transforms.
Geometric Transformations
Transformations Objectives
Geometric Transformations Hearn & Baker Chapter 5
2D Transformations By: KanwarjeetSingh
Computer Graphics Transformations.
2D Transformations with Matrices
3D Geometric Transformations
Projective geometry ECE 847: Digital Image Processing Stan Birchfield
Chapter 5 2-D Transformations.
Computer Graphics Transformations.
3D Transformations Source & Courtesy: University of Wisconsin,
Introduction to Computer Graphics CS 445 / 645
Review: Transformations
2D Transformations y y x x y x.
Homogeneous Coordinates (Projective Space)
Transformations.
Lecture 03: Linear Algebra
COMP 175: Computer Graphics February 9, 2016
With an immediate use for it
CSC4820/6820 Computer Graphics Algorithms Ying Zhu Georgia State University Transformations.
Geometric Camera Models
Chapter IV Spaces and Transforms
2D Geometric Transformations
Chapter 3 Linear Algebra
Transformations Ed Angel
Geometric Objects and Transformations (II)
Transformations Ed Angel Professor Emeritus of Computer Science
with Applications in Computer Graphics
Isaac Gang University of Mary Hardin-Baylor
Transformations.
TWO DIMENSIONAL TRANSFORMATION
Presentation transcript:

2-D Geometry

The Image Formation Pipeline

Outline Vector, matrix basics 2-D point transformations Translation, scaling, rotation, shear Homogeneous coordinates and transformations Homography, affine transformation

Notes on Notation (a little different from book) Vectors, points: x, v (assume column vectors) Matrices: R, T Scalars: x, a Axes, objects: X, Y, O Coordinate systems: W, C Number systems: R, Z Specials Transpose operator: xT (as opposed to x0) Identity matrix: Id Matrices/vectors of zeroes, ones: 0, 1

Block Notation for Matrices Often convenient to write matrices in terms of parts Smaller matrices for blocks Row, column vectors for ranges of entries on rows, columns, respectively E.g.: If A is 3 x 3 and :

2-D Transformations Types Mathematical representation Scaling Rotation Shear Translation Mathematical representation

2-D Scaling

2-D Scaling

2-D Scaling sx 1 Horizontal shift proportional to horizontal position

2-D Scaling sy 1 Vertical shift proportional to vertical position

2-D Scaling

Matrix form of 2-D Scaling

2-D Scaling

2-D Rotation

2-D Rotation µ

2-D Rotation µ

Matrix form of 2-D Rotation µ (this is a counterclockwise rotation; reverse signs of sines to get a clockwise one)

Matrix form of 2-D Rotation µ

2-D Shear (Horizontal)

2-D Shear (Horizontal) Horizontal displacement proportional to vertical position

(Shear factor h is positive for the figure above) 2-D Shear (Horizontal) (Shear factor h is positive for the figure above)

2-D Shear (Horizontal)

2-D Shear (Vertical) (v is negative for the figure above)

2-D Translation

2-D Translation

2-D Translation

2-D Translation

2-D Translation

2-D Translation

Representing Transformations Note that we’ve defined translation as a vector addition but rotation, scaling, etc. as matrix multiplications It’s inconvenient to have two different operations (addition and multiplication) for different forms of transformation It would be desirable for all transformations to be expressed in a common, linear form (since matrix multiplications are linear transformations)

Example: “Trick” of additional coordinate makes this possible Old way: New way:

Translation Matrix We can write the formula using this “expanded” transformation matrix as: From now on, assume points are in this “expanded” form unless otherwise noted:

Homogeneous Coordinates “Expanded” form is called homogeneous coordinates or projective space Technically, 2-D projective space P2 is defined as Euclidean space R3 ¡ (0, 0, 0)T Change to projective space by adding a scale factor (usually but not always 1):

Homogeneous Coordinates: Projective Space Equivalence is defined up to scale, (non-zero for finite points) Think of projective points in P2 as rays in R3, where z coordinate is scale factor All Euclidean points along ray are “same” in this sense

Leaving Projective Space Can go back to non-homogeneous representation by dividing by scale factor and dropping extra coordinate: This is the same as saying “Where does the ray intersect the plane defined by z = 1”?

Homogeneous Coordinates: Rotations, etc. A 2-D rotation, scaling, shear or other transformation normally expressed by a 2 x 2 matrix R is written in homogeneous coordinates with the following 3 x 3 matrix: The non-commutativity of matrix multiplication explains why different transformation orders give different results—i.e., RT  TR In homogeneous form In homogeneous form

Example: Transformations Don’t Commute

Example: Transformations Don’t Commute

Example: Transformations Don’t Commute

Example: Transformations Don’t Commute

2-D Transformations Full-generality 3 x 3 homogeneous transformation is called a homography

Translation components 2-D Transformations Full-generality 3 x 3 homogeneous transformation is called a homography Translation components

Scale/rotation components 2-D Transformations Full-generality 3 x 3 homogeneous transformation is called a homography Scale/rotation components

Shear/rotation components 2-D Transformations Full-generality 3 x 3 homogeneous transformation is called a homography Shear/rotation components Shear/rotation off-diagonal (more about relationship between shearing and rotation at http://splorg.org/people/tobin/projects/israel/projects/paeth/rotation_by_shearing.html)

Homogeneous scaling factor 2-D Transformations Full-generality 3 x 3 homogeneous transformation is called a homography Homogeneous scaling factor

2-D Transformations Full-generality 3 x 3 homogeneous transformation is called a homography When these are zero (as they have been so far), H is an affine transformation