Procedural Cave Generation Juncheng Cui University of Wollongong
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Prime Gradient Noise
Computational Visual Media https://doi.org/10.1007/s41095-021-0206-z Research Article Prime gradient noise Sheldon Taylor1,∗, Owen Sharpe1,∗, and Jiju Peethambaran1 ( ) c The Author(s) 2021. Abstract Procedural noise functions are fundamental 1 Introduction tools in computer graphics used for synthesizing virtual geometry and texture patterns. Ideally, a Visually pleasing 3D content is one of the core procedural noise function should be compact, aperiodic, ingredients of successful movies, video games, and parameterized, and randomly accessible. Traditional virtual reality applications. Unfortunately, creation lattice noise functions such as Perlin noise, however, of high quality virtual 3D content and textures exhibit periodicity due to the axial correlation induced is a labour-intensive task, often requiring several while hashing the lattice vertices to the gradients. months to years of skilled manual labour. A In this paper, we introduce a parameterized lattice relatively cheap yet powerful alternative to manual noise called prime gradient noise (PGN) that minimizes modeling is procedural content generation using a discernible periodicity in the noise while enhancing the set of rules, such as L-systems [1] or procedural algorithmic efficiency. PGN utilizes prime gradients, a noise [2]. Procedural noise has proven highly set of random unit vectors constructed from subsets of successful in creating computer generated imagery prime numbers plotted in polar coordinate system. To (CGI) consisting of 3D models exhibiting fine detail map axial indices of lattice vertices to prime gradients, at multiple scales. Furthermore, procedural noise PGN employs Szudzik pairing, a bijection F : N2 → N. is a compact, flexible, and low cost computational Compositions of Szudzik pairing functions are used in technique to synthesize a range of patterns that may higher dimensions. -
Terrain Synthesis Using Noise Tuomo Hyttinen
Terrain synthesis using noise Tuomo Hyttinen University of Tampere Faculty of Natural Sciences Computer Science M.Sc. Thesis Supervisor: Timo Poranen May 2017 University of Tampere Faculty of Natural Sciences Computer Science Tuomo Hyttinen: Terrain synthesis using noise M.Sc. thesis, 51 pages May 2017 Noise functions are versatile base functions used in many procedural generation methods. They can produce natural-like patterns usable in procedural textures, models and animations. They have been extensively adapted in procedural terrain implementations in games and other applications. Noise-based procedural terrains offer many advantages over static terrain models but designing such terrains is largely unintuitive by nature. Whereas traditional terrain models can be designed, e.g., in spatial editors, procedural terrains are implemented in algorithms. The purpose of this thesis is firstly to evaluate noise functions in the context of procedural terrain generation and especially example based procedural terrain synthesis. Secondly, a novel example based procedural terrain synthesis method is presented. A prototype application implementing the method was also constructed and evaluated. The prototype is a practical solution for example based procedural terrain design, aiming to bridge the gap between intuitive virtual terrain design and the advantages of procedural terrain functions. Key words and terms: noise, procedural terrains, example-based terrain synthesis Contents 1. Introduction......................................................................................................................................1 -
Noisy Gradient Meshes Procedurally Enriching Vector Graphics Using Noise
Noisy Gradient Meshes Procedurally Enriching Vector Graphics using Noise Bachelor Thesis Rowan van Beckhoven Computer Science Faculty of Science and Engineering University of Groningen July 2018 Supervisors: Jirˇ´ı Kosinka Gerben Hettinga Abstract Vector graphics is a powerful approach for representing scalable illustrations. These vector graphics are composed of primitives which define an image. Existing high-level vector graphics primitives are able to model smooth colour tran- sitions well and can be used to vectorise raster images which feature large regions with constant or slowly changing colour gradients. However, when applied to natural images, these methods often result in many small gradient primitives due to high frequency regions present in the image. Working with many gradient primitives becomes a tedious process and thus a solution has to be found in which a high level of detail can be achieved while the underlying mesh remains simple. Procedural noise has been used for texture synthesis before, but it is rarely used in combination with vector graphic primitives. In this research, a gradient mesh is combined with a procedural noise function. i Contents 1 Introduction1 1.1 Gradient Mesh..................................1 1.2 Noise.......................................3 1.2.1 Perlin Noise................................4 1.2.2 Worley Noise...............................4 1.3 Structure of this Thesis..............................5 2 Related Work6 3 Problem Statement8 4 Approach9 5 Implementation 10 5.1 Gradient Mesh Framework............................ 10 5.1.1 Halfedge Structure............................ 10 5.1.2 Framework Extensions.......................... 11 5.2 Pipeline...................................... 12 5.2.1 Noise Field Generation.......................... 13 5.2.2 Distortion................................. 14 5.2.3 Filtering.................................. 15 5.2.4 Colour Mapping............................ -
Polynomial Methods for Fast Procedural Terrain Generation
Polynomial methods for fast Procedural Terrain Generation Yann Thorimbert Bastien Chopard [email protected] December 6, 2018 Abstract A new method is presented, allowing for the generation of 3D ter- rain and texture from coherent noise. The method is significantly faster than prevailing fractal brownian motion approaches, while producing results of equivalent quality. The algorithm is derived through a sys- tematic approach that generalizes to an arbitrary number of spatial dimensions and gradient smoothness. The results are compared, in terms of performance and quality, to fundamental and efficient gradi- ent noise methods widely used in the domain of fast terrain generation: Perlin noise and OpenSimplex noise. Finally, to objectively quantify the degree of realism of the results, a fractal analysis of the generated landscapes is performed and compared to real terrain data. 1 Introduction Procedural terrain generation (PTG) methods have grown in number in the last decades due to the increasing performances of computers; video games, movies and animation find obvious use of PTG, for terrain generation as well as for texture generation. However, a less evident use of PTG can be found in more practical domains, as for instance vehicle dynamics [7] or military training [37, 36], where accurate methods for emulating real ter- rain are of interest. More generally, one can also mention the use made of procedural coherent noise in the field of fluid animation [3, 24], which arXiv:1610.03525v4 [cs.GR] 5 Dec 2018 helps to improve performances of turbulence modeling. The main advan- tages of procedural noise compared to non-procedural noise generation is both an immensely decreased memory demand and an increased amount of content produced. -
Prime Gradient Noise
Computational Visual Media https://doi.org/10.1007/s41095-021-0206-z Vol. 7, No. 3, September 2021, 349–362 Research Article Prime gradient noise Sheldon Taylor1,∗, Owen Sharpe1,∗, and Jiju Peethambaran1 ( ) c The Author(s) 2021. Abstract Procedural noise functions are fundamental 1 Introduction tools in computer graphics used for synthesizing virtual geometry and texture patterns. Ideally, a Visually pleasing 3D content is one of the core procedural noise function should be compact, aperiodic, ingredients of successful movies, video games, and parameterized, and randomly accessible. Traditional virtual reality applications. Unfortunately, creation lattice noise functions such as Perlin noise, however, of high quality virtual 3D content and textures exhibit periodicity due to the axial correlation induced is a labour-intensive task, often requiring several while hashing the lattice vertices to the gradients. months to years of skilled manual labour. A In this paper, we introduce a parameterized lattice relatively cheap yet powerful alternative to manual noise called prime gradient noise (PGN) that minimizes modeling is procedural content generation using a discernible periodicity in the noise while enhancing the set of rules, such as L-systems [1] or procedural algorithmic efficiency. PGN utilizes prime gradients, a noise [2]. Procedural noise has proven highly set of random unit vectors constructed from subsets of successful in creating computer generated imagery prime numbers plotted in polar coordinate system. To (CGI) consisting of 3D models exhibiting fine detail map axial indices of lattice vertices to prime gradients, at multiple scales. Furthermore, procedural noise PGN employs Szudzik pairing, a bijection F : N2 → N. is a compact, flexible, and low cost computational Compositions of Szudzik pairing functions are used in technique to synthesize a range of patterns that may higher dimensions. -
Hardware-Accelerated Gradient Noise for Graphics
Hardware-Accelerated Gradient Noise for Graphics Josef B. Spjut Andrew E. Kensler Erik L. Brunvand School of Computing SCI Institute School of Computing University of Utah University of Utah University of Utah [email protected] [email protected] [email protected] ABSTRACT techniques trade computation for memory. This is impor- A synthetic noise function is a key component of most com- tant since as process technology scales, compute resources puter graphics rendering systems. This pseudo-random noise will increasingly outstrip memory speeds. For texturing sur- function is used to create a wide variety of natural looking faces, the memory reduction can be two-fold: first there textures that are applied to objects in the scene. To be is the simple reduction in texture memory itself. Second, useful, the generated noise should be repeatable while ex- 3D or \solid" procedural textures can eliminate the need for hibiting no discernible periodicity, anisotropy, or aliasing. explicit texture coordinates to be stored with the models. However, noise with these qualities is computationally ex- However, in order to avoid uniformity and produce visual pensive and results in a significant fraction of the run time richness, a simple, repeatable, pseudo-random function is for scenes with rich visual complexity. We propose modifi- required. Noise functions meet this need. Simply described, a noise function in computer graphics cations to the standard algorithm for computing synthetic N noise that improve the visual quality of the noise, and a par- is an R ! R mapping used to introduce irregularity into allel hardware implementation of this improved noise func- an otherwise regular pattern. -
Terrain Synthesis Using Noise
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Trepo - Institutional Repository of Tampere University Terrain synthesis using noise Tuomo Hyttinen University of Tampere Faculty of Natural Sciences Computer Science M.Sc. Thesis Supervisor: Timo Poranen May 2017 University of Tampere Faculty of Natural Sciences Computer Science Tuomo Hyttinen: Terrain synthesis using noise M.Sc. thesis, 51 pages May 2017 Noise functions are versatile base functions used in many procedural generation methods. They can produce natural-like patterns usable in procedural textures, models and animations. They have been extensively adapted in procedural terrain implementations in games and other applications. Noise-based procedural terrains offer many advantages over static terrain models but designing such terrains is largely unintuitive by nature. Whereas traditional terrain models can be designed, e.g., in spatial editors, procedural terrains are implemented in algorithms. The purpose of this thesis is firstly to evaluate noise functions in the context of procedural terrain generation and especially example based procedural terrain synthesis. Secondly, a novel example based procedural terrain synthesis method is presented. A prototype application implementing the method was also constructed and evaluated. The prototype is a practical solution for example based procedural terrain design, aiming to bridge the gap between intuitive virtual terrain design and the advantages of procedural terrain functions. Key words