CSCE 552 Spring 2011 Math By Jijun Tang. Layered

CSCE 552 Spring 2011

Math

By Jijun Tang

Layered

Initialization/Shutdown

Resource Acquisition Is Initialization A useful rule to minimalize mismatch errors in the

initialization and shutdown steps Means that creating an object acquires and

initializes all the necessary resources, and destroying it destroys and shuts down all those resources

Optimizations Fast shutdown Warm reboot

Main Game Loop

Structure Hard-coded loops Multiple game loops: for each major game state Consider steps as tasks to be iterated through

Coupling Can decouple the rendering step from simulation

and update steps Results in higher frame rate, smoother animation,

and greater responsiveness Implementation is tricky and can be error-prone

Math

Applied Trigonometry

Trigonometric functions Defined using right triangle

x

yh

Applied Trigonometry

Angles measured in radians

Full circle contains 2 radians

Applied Trigonometry

Sine and cosine used to decompose a point into horizontal and vertical components

r cos

r sin r

x

y

Trigonometry

Trigonometric identities

Inverse trigonometric functions

Return angle for which sin, cos, or tan function produces a particular value

If sin = z, then = sin-1 z

If cos = z, then = cos-1 z

If tan = z, then = tan-1 z

arcs

Applied Trigonometry

Law of sines

Law of cosines

Reduces to Pythagorean theorem when = 90 degrees

b

a

c

Vectors and Scalars

Scalars represent quantities that can be described fully using one value Mass Time Distance

Vectors describe a magnitude and direction together using multiple values

Examples of vectors

Difference between two points Magnitude is the distance between the points Direction points from one point to the other

Velocity of a projectile Magnitude is the speed of the projectile Direction is the direction in which it’s traveling

A force is applied along a direction

Visualize Vectors

The length represents the magnitude The arrowhead indicates the direction Multiplying a vector by a scalar

changes the arrow’s length

V

2V

–V

Vectors Add and Subtraction

Two vectors V and W are added by placing the beginning of W at the end of V

Subtraction reverses the second vector

V

WV + W

V

W

V

V – W–W

High-Dimension Vectors

An n-dimensional vector V is represented by n components

In three dimensions, the components are named x, y, and z

Individual components are expressed using the name as a subscript:

1 2 3x y zV V V

Add/Subtract Componentwise

Vector Magnitude

The magnitude of an n-dimensional vector V is given by

In three dimensions, this is

Vector Normalization

A vector having a magnitude of 1 is called a unit vector

Any vector V can be resized to unit length by dividing it by its magnitude:

This process is called normalization

Matrices

A matrix is a rectangular array of numbers arranged as rows and columns

A matrix having n rows and m columns is an n m matrix At the right, M is a

2 3 matrix If n = m, the matrix is a square matrix

Matrix Representation

The entry of a matrix M in the i-th row and j-th column is denoted Mij

For example,

Matrix Transpose

The transpose of a matrix M is denoted MT and has its rows and columns exchanged:

Vectors and Matrices

An n-dimensional vector V can be thought of as an n 1 column matrix:

Or a 1 n row matrix:

Vectors and Matrices

Product of two matrices A and B Number of columns of A must equal

number of rows of B Entries of the product are given by

If A is a n m matrix, and B is an m p matrix, then AB is an n p matrix

Vectors and Matrices

Example matrix product

Vectors and Matrices

Matrices are used to transform vectors from one coordinate system to another

In three dimensions, the product of a matrix and a column vector looks like:

Identity Matrix In

For any n n matrix M,

the product with the

identity matrix is M itself InM = M

MIn = M

Invertible

An n n matrix M is invertible if there exists another matrix G such that

The inverse of M is denoted M-1

1 0 0

0 1 0

0 0 1

n

MG GM I

Properties of Inverse

Not every matrix has an inverse A noninvertible matrix is called singular Whether a matrix is invertible can be

determined by calculating a scalar quantity called the determinant

Determinant

The determinant of a square matrix M is denoted det M or |M|

A matrix is invertible if its determinant is not zero

For a 2 2 matrix,

deta b a b

ad bcc d c d

Determinant

The determinant of a 3 3 matrix is

Inverse

Explicit formulas exist for matrix inverses These are good for small matrices, but

other methods are generally used for larger matrices

In computer graphics, we are usually dealing with 2 2, 3 3, and a special form of 4 4 matrices

Inverse of 2x2 and 3x3

The inverse of a 2 2 matrix M is

The inverse of a 3 3 matrix M is

4x4

A special type of 4 4 matrix used in computer graphics looks like

R is a 3 3 rotation matrix, and T is a translation vector

11 12 13

21 22 23

31 32 33

0 0 0 1

x

y

z

R R R T

R R R T

R R R T

M

Inverse of 4x4

1 1 1 111 12 13

1 1 1 1 1 121 22 23

1

1 1 1 131 32 33

1 0 0 0 1

x

y

z

R R R

R R R

R R R

R T

R R T R TM

R T

0

General Matrix Inverse

(AB) -1 = B-1A-1

A general nxn matrix can be inverted using methods such as Gauss-Jordan elimination Gaussian elimination LU decomposition

Gauss-Jordan Elimination

Gaussian Elimination

The Dot Product

The dot product is a product between two vectors that produces a scalar

The dot product between twon-dimensional vectors V and W is given by

In three dimensions,

Dot Product Usage

The dot product can be used to project one vector onto another

V

W

Dot Product Properties

The dot product satisfies the formula

is the angle between the two vectors Dot product is always 0 between

perpendicular vectors If V and W are unit vectors, the dot

product is 1 for parallel vectors pointing in the same direction, -1 for opposite

Self Dot Product

The dot product of a vector with itself produces the squared magnitude

Often, the notation V 2 is used as shorthand for V V

The Cross Product

The cross product is a product between two vectors the produces a vector

The cross product only applies in three dimensions The cross product is perpendicular to both

vectors being multiplied together The cross product between two parallel

vectors is the zero vector (0, 0, 0)

Illustration

The cross product satisfies the trigonometric relationship

This is the area ofthe parallelogramformed byV and W

V

W

||V|| sin

Area and Cross Product

The area A of a triangle with vertices P1, P2, and P3 is thus given by

Rules

Cross products obey the right hand rule If first vector points along right thumb, and

second vector points along right fingers, Then cross product points out of right palm

Reversing order of vectors negates the cross product:

Cross product is anticommutative

Rules in Figure

Formular

The cross product between V and W is

A helpful tool for remembering this formula is the pseudodeterminant (x, y, z) are unit vectors

Alternative

The cross product can also be expressed as the matrix-vector product

The perpendicularity property means