67 research outputs found
Procedural Generation of 3D Caves for Games on the GPU
Procedural Content Generation in Games (PCG) is a thriv- ing field of research and application. Recent presented ex- amples range from levels, stories and race tracks to complete rulesets for games. However, there is not much research to date on procedural 3D modeling of caves, and similar en- closed natural spaces. In this paper, we present a modular pipeline to procedurally generate underground caves in real- time, to be used as part of larger landscapes in game worlds. We propose a three step approach, which can be fully im- plemented using General-Purpose Computing on Graphics Processing (GPGPU) technology: 1) an L-System to em- ulate the expanded cracks and passages which form cave structures in nature, 2) a noise-perturbed metaball approach for virtual 3D carving, and 3) a rendering component for isosurface extraction of the modeled voxel data, and fur- ther mesh enhancement through shader programming. We demonstrate how the interaction between these components produce results comparable to real world caves, and show that the solution is viable for video game environments. For this, we present the findings of a user study we conducted among indie-game developers and players, using our results
A framework for digital watercolor
This research develops an extendible framework for reproducing watercolor in a digital
environment, with a focus on interactivity using the GPU. The framework uses the
lattice Boltzmann method, a relatively new approach to fluid dynamics, and the
Kubelka-Munk reflectance model to capture the optical properties of watercolor. The
work is demonstrated through several paintings produced using the system
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General Purpose Programming on Modern Graphics Hardware
I start with a brief introduction to the graphics processing unit (GPU) as well as general-purpose computation on modern graphics hardware (GPGPU). Next, I explore the motivations for GPGPU programming, and the capabilities of modern GPUs (including advantages and disadvantages). Also, I give the background required for further exploring GPU programming, including the terminology used and the resources available. Finally, I include a comprehensive survey of previous and current GPGPU work, and end with a look at the future of GPU programming
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