Full metadata
Title
Procedural Content Generation Using Noise
Description
Procedural content generation refers to the creation of data algorithmically using controlled randomness. These algorithms can be used to generate complex environments and geological formations as opposed to manually creating environments, using photogrammetry, or other means. Geological formations and the surrounding terrain can be created using noise based algorithms such as Perlin noise. However, interpreting noise in this manner has a number of challenges due to the pseudo-random nature of noise. We will discuss how to generate noise, how to render noise, and the challenges in interpreting noise.
Date Created
2021-05
Contributors
- Li, Michael L (Author)
- Hansford, Dianne (Thesis director)
- Kobayashi, Yoshihiro (Committee member)
- Computer Science and Engineering Program (Contributor, Contributor)
- School of Art (Contributor)
- Barrett, The Honors College (Contributor)
Topical Subject
Resource Type
Extent
51 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2020-2021
Handle
https://hdl.handle.net/2286/R.I.63930
Level of coding
minimal
Cataloging Standards
System Created
- 2021-04-24 12:28:59
System Modified
- 2021-08-11 04:09:57
- 3 years 3 months ago
Additional Formats