Rotation is the transformation along circular paths.
Rotation angle
determines the amount of rotation for
each vertex.
be any point on the plane.
Then the rotation of the point P about an angle
about the origin maps it onto a point
From the figure, it is obvious that

Equating (
) and (
), we
get the equation of rotation about an angle
.
Equation (
) can be expressed in
matrix
form.

is the rotation of the matrix about the origin
through an angle
Example
If
is rotated about an angle
,
determine the image point.

Rotation matrix is given by

Substituting the above values in equation (
)

Therefore, the image point is given by
, every point of the plane
remains unaffected.
yields matrix of
the form

and that through
is an
identity matrix

To rotate a point
by an angle
about an arbitrary axis v that passes through the
origin
so that v coincides
with the origin.


3-Dimensional rotation provide flexible views of 3D objects. Rotation in 3D is quite complex than that in 2D. In 2D, the centre of rotation is fixed. However in 3D, the axis and the angle of rotation has to be defined. When one of the positive x, y, z coordinate is chosen as the axis of rotation, then the rotation is similar to that of 2D. The general convention is that the positive rotation is counter clockwise.
Rotation about Z axis is rotating every point from X to Y. The rotation matrix is given by

Rotation about X axis is rotating every point from Y to Z. The rotation matrix is given by

Rotation about Y axis is rotating every point from Z to X. The rotation matrix is given by

Let P be any point in the YZ plane. Rotation of the
point about an arbitrary axis
is done as follows
so that it is aligned with
Z axis. This is done in two steps
through
about Z axis
so that it is in XZ plane.

through
about Y axis,
so that it is aligned with Z axis.


to its original direction. This is
done by rotating in the reverse direction through an angle of
and
.
The rotation matrix
about an arbitrary axis u
through an angle A is obtained as one matrix by
multiplying all the transformation matrices mentioned above.

Translate points along a straight line
Scale the distance of points from an origin
Skew points relative to an axis.
Project points from 3D to 2D