Graphics Reference
In-Depth Information
Image
Vertices ~5500
~2880
~1580
~670
140
Maximum detail,
for closeups.
Minimum detail,
very far objects.
Notes
FIGURE 3.1 Visual effect of varying vertex count for 3D object in discrete steps. (Source:
http://en.wikipedia.org/wiki/Level_of_detail#A_discrete_LOD_example)
experience offered by a real-time rendering application. While the quality of the
generated imagery may be important to the user, the interactive experience is usu-
ally dominated by the application response rather than the quality of the generated
imagery. Furthermore, quality is a subjective notion that complicates the adequacy
of any useful metric.
3.4 LINEAR SYSTEM MODEL REPRESENTATION
FOR REAL-TIME RENDERING
This section describes the modelling process applied to the real-time rendering
system and the derivation of the mathematical models for various types of rendering
applications. Using the system identification methodology, we demonstrate that lin-
ear time-invariant models can be obtained from the input and output data collected
from experiments conducted using sample rendering applications.
A basic relationship between the input and output of a system may be expressed
as a linear difference equation as follows.
() +
(
) +…
(
) =
(
) +…+
(
) 1  () (3.1)
yt
ay t
1
a
yt n
ut n
b ut n
n
b +
e t
1
n
a
1
k
n
k
a
b
where:
a 1 a n a and b 1 b n b are parameters to be estimated.
y ( t ) is the output of the system at time t.
yt
(
1 and yt n a
(
)   are the previous outputs on which the current output depends.
(
) and ut nn
(
1 are the previous inputs on which the current output
ut n k
−−+
k
b
depends.
n a is the number of poles of the system or the order of the system.
n b represents the number of zeroes plus one.
n k denotes delay in the system.
e ( t ) equals noise.
An alternative way to represent Equation (3.1) in a more compact manner is the ARX
model described below:
() () =
()
(
) + ()
Aq yt
Bqut net
k
(3.2)
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