Publication Details
Building Triangle Strips Using Hopfield Neural Network
Zbořil František, doc. Ing., CSc. (DITS)
Visualization, triangle strips, Hopfield neural network
The most common way to visualize three dimensional data in graphics systems is to
use triangles. Firstly, the data is converted to a set of triangles. Each time
the visualization is accomplished this set is sent to graphics hardware
repeatedly. The speed of final visualization is limited by the rate at which the
data is sent to hardware. The responsiveness of interactive applications such as
virtual reality, games, etc. is highly sensitive to visualization speed.
Therefore, it is crucial to optimize visualized data to reduce rendering time.
One of the way to optimize rendered data supported by current graphics pipelines
is to use triangle strips. Constructing optimal set of triangle strips is
NP-complete problem. This paper deals with constructing such primitives using
Hopfield neural network.
@inproceedings{BUT21439,
author="Dominik {Pospíšil} and František {Zbořil}",
title="Building Triangle Strips Using Hopfield Neural Network",
booktitle="Proceedings of the Sixth International Scientific Conference ECI 2004",
year="2004",
pages="394--398",
publisher="Faculty of Electrical Engineering and Informatics, University of Technology Košice",
address="Košice",
isbn="80-8073-150-0"
}