Procedural Generation and Rendering of Large-Scale Open-World Environments

Open-world video games give players a large environment to explore along with increased freedom to navigate and manipulate that environment. These requirements pose several problems that must be addressed by a game\u27s graphics engine. Often there are a large number of visible objects, such as all of the trees in a forest, as well as objects comprised of large amounts of geometry, such as terrain. An open-world graphics engine must be able to render large environments at varying levels of detail and smoothly transition between detail levels to provide a believable experience. Often this involves finding a way to both store and generate the large amounts of geometry that represent the environment. In this thesis we present a system for generating and rendering large exterior environments, with a focus on terrain and vegetation. We use a region-based procedural generation algorithm to create environments of varying types. This algorithm produces content that can be rendered at multiple levels of detail. The terrain is rendered volumetrically to support caves, overhangs, and cliffs, but is also rendered using heightmaps to allow for large view distances. Vegetation is implemented using procedurally generated meshes and impostors. The volumetric terrain is editable in real time, which limits our ability to pre-generate or cache large amounts of geometry, and also limits the number of assumptions we can make with regard to visibility. We support a view distance of at least 25 miles in each direction, though distant objects are rendered at low resolution. The heightmap terrain used to achieve this view distance consists of over 360,000 triangles. Our system runs at 180 frames per second on commodity desktop hardware

Procedural feature generation for volumetric terrains using voxel grammars

© 2018 Terrain generation is a fundamental requirement of many computer graphics simulations, including computer games, flight simulators and environments in feature films. There has been a considerable amount of research in this domain, which ranges between fully automated and semi-automated methods. Voxel representations of 3D terrains can create rich features that are not found in other forms of terrain generation techniques, such as caves and overhangs. In this article, we introduce a semi-automated method of generating features for volumetric terrains using a rule-based procedural generation system. Features are generated by selecting subsets of a voxel grid as input symbols to a grammar, composed of user-created operators. This results in overhangs and caves generated from a set of simple rules. The feature generation runs on the CPU and the GPU is utilised to extract a robust mesh from the volumetric dataset

Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications

We present an overview and evaluation of a new, systematic approach for generation of highly realistic, annotated synthetic data for training of deep neural networks in computer vision tasks. The main contribution is a procedural world modeling approach enabling high variability coupled with physically accurate image synthesis, and is a departure from the hand-modeled virtual worlds and approximate image synthesis methods used in real-time applications. The benefits of our approach include flexible, physically accurate and scalable image synthesis, implicit wide coverage of classes and features, and complete data introspection for annotations, which all contribute to quality and cost efficiency. To evaluate our approach and the efficacy of the resulting data, we use semantic segmentation for autonomous vehicles and robotic navigation as the main application, and we train multiple deep learning architectures using synthetic data with and without fine tuning on organic (i.e. real-world) data. The evaluation shows that our approach improves the neural network's performance and that even modest implementation efforts produce state-of-the-art results.Comment: The project web page at http://vcl.itn.liu.se/publications/2017/TKWU17/ contains a version of the paper with high-resolution images as well as additional materia