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
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2021-05
Agent
- Author (aut): Li, Michael L
- Thesis director: Hansford, Dianne
- Committee member: Kobayashi, Yoshihiro
- Contributor (ctb): Computer Science and Engineering Program
- Contributor (ctb): School of Art
- Contributor (ctb): Computer Science and Engineering Program
- Contributor (ctb): Barrett, The Honors College