R E L S O F T ’ S Q U I C K B A S I C 3 D
T U T O R I A L S E R I E S
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C H A P T E R 4
Introduction
Matrices are useful in 3d graphics. Not only are they fast, but once you get
used to them, it makes things a lot simpler. Matrices are better than standard
equations for these reasons:
1.
Actions(transformations) such as scaling, rotation and translation can be easily
kept track because you only need to keep track of the matrix and forget about
your 3d coordinates.
2. It's a onepass transform. Which means you can make as many matrices as you want and combine it in one single matrix to do all the transformations for you. Simplicity at its best!!!
3. You
are not limited to just the XYZ angle system when viewing your virtual world.
You could make a Lookat function to make
things even simpler!!!(I'll get to that in another article)
For this article, I'm going to discuss matrices and their applications. I'm
gonna start with the use of matrices in solving systems of linear equations, the
basic operations on matrices and their applications in 3d graphics. I might be
able to put in some code and algos in between. Don't worry, matrices are not as
hard as you thought they are. :*). I'm gonna be discussing those things you'd
need in making a 3d game engine using matrices. Which means that most matrix
stuff I'm going to include in here are the easy ones. So without further
ado....
Systems of linear equations
Remember the linear
equation...
ax + by = c?
No? How about
this?
y = mx +
b?
This two equations
are just two of the many forms of linear equations. The first one(ax+by=c) is the "standard" form and y=mx+b is the "slopeintercept" form. We'll be discussing the
standard form when dealing with matrices.
Given 2
equations:
2x
 3y = 1
and
3x + 2y = 8
How do you get the solution to both equations? The solution is actually the "intersection" of both lines defined by the above equations. For those who have done some algebra, we know that there are a number of ways to find the solution.
They are:
1.
Graphing
2. Substitution
3. Elimination
Solving
via elimination:
2x  3y = 1 equ 1
3x + 2y = 8
equ 2
Make the
coeficients of x the same by multiplying equ 1 by 3 and equ 2 by 2 then
subtract.
3*[2x  3y = 1]*3
2*[3x + 2y = 8]*2
6x  9y = 3
6x + 4y
= 16


13y = 13 > /13
y = 1
Using back substitution(equ 1):
2x  3(1) =
1
2x = 1 + 3 >/2
x = 2
The solution is
(2,1)
However when made into code, this is very cumbersome and not flexible. What we
need is an algorithmic way to solve the system. And the answer is the matrix.
How do we go about solving this system using a matrix? First let me discuss the
ECHELON method of solving this system as it's almost
parallel to the matrix method except for the last part.
Solving via
the Echelon
method:
2x  3y = 1
equ 1
3x + 2y = 8 equ 2
1. Multiply
both sides of equ 1 by 1/2 so that x will have a coefficient of
1.
x  3/2y = 1/2 equ 3
3x + 2y = 8
2. Eliminate x from equ 2 by adding (3)
times equ 3 to equ 2.
3 *[x  3/2y =
1/2]*
3
=
3x + 9/2y =
3/2
3x + 2y = 8 > make 2y and 8
similar to 9/2 y and 3/2.
ie. 2y= 4/2y
; 8 =
16/2
3x + 9/2y =
3/2
3x + 4/2y =
16/2

13/2y =
13/2
y = 1
equ 4
so.
x  3/2y = 1/2 equ
3
y = 1
equ 4
* Using back
substitution in equ 1, x =
2.
* look at the coefficients of x and y.
They both have coefficients of 1 arranged diagonally.
ie..
1x + y =
c
1y = c
This is called
the TRIANGULAR or LOW ECHELON form of the system. Be sure to remember this as we
well be encountering this a lot of times. And now, what you've been waiting
for!!!!
Solving the system the Matrix way!!!
RULES:
A. Any two rows may be interchanged. This is useful if one of the equations' xterm has a coefficient of 1.
B. The Elements of any row may be multiplied by any nonzero real number.
C. Any row may be changed b
adding to its elements a multiple of the elements of another
row.
2x  3y =
1 equ 1
3x + 2y = 8 equ 2
1. We first write the system in rows
and columns. This is called the AUGMENTED matrix. Be sure that each
equation is in standard form (ax + by =
c).
* This is parallel to the Echelon method above so be
sure to check from time to time.
2  3  1 
3  2  8 
*Note we only used the numeric coefficients.
*2,
3, 1 , 3, 2 and 8 are called the ELEMENTS of the matrix and 2 is located
at row1,col1; 8 at row2, col3; and so on...
2. To get 1 in row1, col1 we
multiply the first row by 1/2.
1  3/2  1/2 
3  2  8 
3. Add (3) times the elements of row1 to
row2.
1  3/2  1/2 
0  13/2  13/2 
4. To get 1 in row 2, col 2; multiply row 2 by
the reciprocal of 13/2 which is 2/13.
1  3/2  1/2 
0  1  1 
So...
x  3/2y =
1/2
y = 1
See, triangular form!!!
Use back substitution to
get x.
I'll test your skills with a 3equation system:
x + y  z =
6
2x  y + z =
9
x  2y + 3z = 1
We don't need to change the element i r1,c1
since it's already 1.
BTW, you can interchange any rows as you like if it
makes the solution easier(RuleA).
Augmented matrix:
1  1  1  6 
2  1  1  9 
1  2  3  1 
1. Eliminate the first element in row 2 by adding (2) x row 1 to row 2.
1  1  1  6 
0  3  3  21 
1  2  3  1 
2. Eliminate the first element in row 3 by adding (1) x row 1 to row 3.
1  1  1  6 
0  3  3  21 
0  3  4  5 
3. To get 1 in row2,col2; Multiply
row 2 by 1/3.
1  1  1  6 
0  1  1  7 
0  3  4  7 
4. Eliminate the second element in
row 3 by adding (3) x row 2 to row 3.
1  1  1  6 
0  1  1  7 
0  0  1  16 
5. Translating this matrix to equation
form:
x + y  z =
6
y  z =
7
z = 16
(This is the triangular form of the
equations)
*The method I discussed above is called the "GAUSSIAN
REDUCTION". If you don't know who Karl F. Gauss is then this
article is not for you. :*) j/k
Properties of
Matrices
It is customary to name Matrices with capital letters. The following is Matrix
A.
a11  a12  a13  a14  
A =  a21  a22  a23  a24 
a31  a32  a33  a34  
a41  a42  a43  a44 
With this notation, the first row and first column is a11(read: "a sub
oneone).
Matrices are classified according to size(by the number of rows and columns
they contain). For example matrix A is a 4 x 4 Matrix. On the other hand our
matrix solution above is a 2 x 3 matrix:
1  3/2  1/2 
0  1  1 
Certain matrices have special names like a SQUARE matrix as in 3 x 3, 2 x
2, Basically the same number of row and columns. A ROW matrix on the other hand
is just a matrix of one row. Guess what a COLUMN matrix is? :*)
Operations on
Matrices
A. Addition of
matrices
To add two matrices together, add their corresponding elements. ONLY
MATRICES OF THE SAME SIZE CAN BE ADDED. Same goes for
subtraction.
5  6 
8  9 
+
4  6 
8  3 
=
5+(4)  6+6 
8+8  9+(3) 
=
1  0 
16  6 
B. Multiplication of a
Matrix by a scalar
value.
To multiply a scalar value by a matrix, you just multiply all elements of the
matrix by the scalar value.
5 *  2  3  =  10  15  
0  4  0  20 
C. Multiplication of
Matrices
RULE. You can only
multiply matrices if A has the same number of columns as B. ROW by
COLUMN.
Ohh this is gonna be *messy*.
:*)
Given:
A =  3  4  2 
5  0  4 
6  4  
B =  2  3 
3  2 
1. Locate row1 of A and col1 of B,
then multiply corresponding elements and add the products.
Row 1
of A
3  4  2 
*
Column 1
of B
6  2  3 
=
(3)(6)  +  (4)(2)  +  (2)(3)  =  32 
2. Next Row1 of A by Col2 of B
(3)(4)  +  (4)(3)  +  (2)(2)  =  4 
+ + =
3. Row 2 of A
and Col 1 of B
(5)(6)  +  (0)(2)  +  (4)(3)  =  18 
4. Lastly, Row 2 of a and col 2 of
B
(5)(4)  +  (0)(3)  +  (4)(2)  =  12 
The product matrix:
32  4 
18  12 
In general...
Cij = Ai1*B1j
+
Ai2*B2j ...
For Square matrices, there are two ways to multiply as they have the same number of rows and columns. Warning: Multiplication of matrices is not commutative.
So in two 4*4 matrices, the resulting matrix is
calculated as...
QBcode:
SUB Matrix.MulMatrix (M!(),
TM!())
'Combines 2 matrices M!() and
TM!()
'ie. Result = TM x M
'Warning
matrix multiplication is not commutative.
'M x TM <>
TM x M
DIM Result!(1 TO 4, 1 TO 4) 'resultant
matrix to be copied to M!()
FOR i = 1 TO
4
FOR j = 1 TO
4
Result!(i, j) =
0
FOR k = 1 TO
4
Result!(i, j) = Result!(i, j) + TM!(i, k) * M!(k,
j)
NEXT k
NEXT j
NEXT i
Now that we know how to do stuff with matrices, we will now learn its
applications is 3d graphics!!!!
Woot!!!
In 3d graphics its often easier to make the origin(0,0,0) as your viewpoint. ie. Where the lens of your
camera is(The LEFTHANDED system lends itself well with this if you want to
make a doomlike engine). Instead of making the camera move around
your world, you can make your world move around the camera. Relativity at its
best!!!
Your first
coordinate
Unless you want to do shearing and some other special effects, it's convenient
to represent your 3d point/vector as [x y z]. I like to make this vector
as a column matrix(see column matrix above). Modifying the points position is
space requires another matrix. For simplicity, I'll make the the transfomation
matrix a ROW matrix, [A B C]. To transform a point, you just multiply the
our [x,y,z] vector with the with our ROW matrix. Remember our matrix
multiplication property? COLUMN x ROW.
x  
y  *  A  B  C 
z 
= x*A + y*B +
z*C
Now if a = 1, b=0, c=0
x*1 + y*0
+ z*0 = x
If a = 0, b=1, c=0
x*0 +
y*1 + z*0 = y
If a = 0, b=0, c=1
x*0
+ y*0 + z*1 = z
In matrix form:
1  0  0  >x row vector A 
0  1  0  >y row vector B 
0  0  1  >z row vector C 
*Notice how it looks like the "Triangular"
form of the matrix.
:*)
So to transform and entire 3d point by the vector matrix using the matrix
notation above, you just multiply the point vector by the
matrix.
*x',y',z' are the new points.
x  m11  m12  m13  x'  
y  *  m21  m22  m23  =  y' 
z  m31  m32  m33  z' 
=
x' =
x*m11 +
y*m12 +
z*m13
y' =
x*m21 +
y*m22 +
z*m23
z' = x*m31 + y*m32 + z*m33
Now as we will be using a 4x4 matrix, let me introduce you to the matrices we'll
be using.
1. The IDENTITY
matrix
Our initial "donothing" matrix. This means that it will produce exactly
the same values as was before the transform. We always begin with this
matrix.
1  0  0  0  > x'= x 
0  1  0  0  > y'= y 
0  0  1  0  > z'= z 
0  0  0  1 
Unless you'd want to do some nasty FX like Shearing,etc., the last row is always
0 0 0 1.
2. The
Scaling matrix
Scales the matrix by
sx,sy and sz.
sx  0  0  0  > x'= x * sx 
0  sy  0  0  > y'= y *sy 
0  0  sz  0  > z'= z * sz 
0  0  0  1 
3. The Translation
matrix.
Translation means just to "move" the point by Tx, Ty,
Tz.
1  0  0  Tx  > x'= x + Tx 
0  1  0  Ty  > y'= y + Ty 
0  0  1  Tz  > z'= z + Tz 
0  0  0  1 
4. The Xaxis rotation
matrix
Rotates the points in
the xaxis by angle.
ca = COS(angle)
sa =
SIN(angle)
1  0  0  0  > x'= x 
0  ca  sa  0  > y'= ca * y  s*z 
0  sa  ca  0  > z'= sa * y + ca * z 
0  0  0  1 
5. The Yaxis rotation
matrix
ca  0  sa  0 
> x'= ca * x + sa * z 
0  1  0  0 
> y'= y 
sa  0  ca  0 
> z'= sa * x + ca * z 
0  0  0  1 
6. The Zaxis rotation
matrix
ca  sa  0  0  > x'= ca * x  sa * y 
sa  ca  0  0  > y'= sa * x + ca * y 
0  0  1  0  > z'= z 
0  0  0  1 
Note that the axis of rotation is NOT being transformed in the 3 rotational
matrices. Now with all the abstract math out of the way, the fun
part....
Applications
To make a 3d object rotate around space using matrices, You just combine all the
transformation matrices into one final parent matrix and use that matrix to
transform your points. Here's the PseudoCODE:
PseudoCODE:
Matrix!() is our
final combined matrix
Tmatrix!() is a temporary matrix used for
transformation.
Dim
Matrix!(1 to 4, 1 to 4)
Dim TMatrix!(1 to 4, 1 to
4)
1. Set Matrix! and Tmatrix
as Identity matrices.
2. Set
Tmatrix! as Scaling matrix
3.
Multiply Matrix! and Tmatrix!
4.
Set Tmatrix! as Translate matrix
5. Multiply Matrix! and Tmatrix!
6. Set Tmatrix! as RotX matrix
7. Multiply Matrix! and Tmatrix!
8. [6] but RotY then [7]
9. [6] but ROTZ then [7]
10. For i =0 to numpoints
11. TransformPoints using
Matrix
12.
Project points
13. next
i
*Codes 2 to 9 can be interchanged in any way you want. If you have normals you'd
like to rotate, you can use the same transformation matrix to rotate them. I
urge you to experiment and play with the order of operations so that you may see
how it changes the entire transformation.
Here's the working QBcode for
you to enjoy.
MatrxRot.Bas
As an excersise, why don't you make a gouraud filled polygon using matrices
to rotate your model and normals? Be sure to rotate with the same matrix.
You might
say, "But your rotation tutorial has some very fast readymade matrix constants.
It's also fairly faster as we don't have to multiply matrices." Yes those
constants are faster than the matrix method but they are limited. Here are some
limitations:
1. Those constants have a fixed order of rotation(x,y and then z). If you want
to change the order of rotation, you need to do the "messy" factoring I did
again. With matrices all you have to do is change the order and that's it.
Simple as it can
get.
2. To translate points from the camera, you have to subtract your camera vector
from your transformed points manually. The matrix way would just use the
translation
matrix.
3. To translate from the origin, you'd have to subtract a translation vector
manually from the original nonrotated points while with matrices, you just
translate before rotate.
:*)
4.
Those constants are limited to angular viewing systems while matrices can handle
any viewing system. Most popular of them is the LOOKAT
transform(I'll get to that in the next
article).
5. The speed difference is not apparent considering all the calculations in both
methods are *outside* your rasterizing loop. I
never lost a single frame myself. The more the points to transform, the less
difference it makes.
Some of you may have already seen Matrices
defined like this:
Translation
matrix:
1  0  0  0 
0  1  0  0 
0  0  1  0 
Tx  Ty  Tz  1 
This is the DirectX and OpenGL system of matrices where rows are swapped with
the columns. So be sure to use this system if you're coding via DX or OGL. I'm
using the "standard" math notation in this
article.
Credits:
Mark Feldman for his matrix doc. ( I was having problems with the rotation matrices
until I read your doc. Thanks!!!)
Plasma for
SetVideoSeg
wildcard for this "series" idea.
Hugo Elias for his WuPixel
doc.
Toshi for his kind comments.
3D ica for there excellent doc.
And you the reader of this doc.
Biskbart for the torus.
Happy
Coding!!!!
Richard Eric M. Lope (Relsoft)
http://rel.betterwebber.com/
vic_viperph@yahoo.com
*For
questions and suggestions, I hang out at Qbasicnews.com > forum.
Http://Forum.Qbasicnews.com