Using Genetic Algorithms to Optimise Triangle Strips
Lord, Kieren J. & Brown, Ross A. (2005) Using Genetic Algorithms to Optimise Triangle Strips. In Geoff, Wyvill, David, Arnold, & Mark, Bilinghurst (Eds.) 3rd International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia, November 29 - December 2, 2005, Dunedin, New Zealand.
There is an ever increasing demand for higher levels of visual detail in graphical applications, particularly in computer games and applications employing visualisation. Triangle strips have been commonly used to optimise the rendering of large geometric meshes. This paper investigates the process of generating optimal triangle strips through the use of genetic algorithms (GA), to remove the need for special knowledge of the intended hardware platform. Two methods – L-System encoding and parameter tuning of an established algorithm were implemented and tested. The results of this work show that over an extended period of time, solutions can be achieved that are comparable to existing triangle stripping techniques, but the best results were obtained from using the GA to tune the parameters of an existing triangle stripping algorithm.
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||Triangle Strip Optimisation, Genetic Algorithms, L, Systems|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)|
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Graphics (080103)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2005 ACM Press|
|Copyright Statement:||Reproduced in accordance with the copyright policy of the publisher.|
|Deposited On:||16 Dec 2005|
|Last Modified:||29 Feb 2012 23:12|
Repository Staff Only: item control page