Mountain View, California 9403 In standard fractal terrain models based on fractional d Brownian motion the statistical character of the surface is, by esign, the same everywhere. A new approach to the synthesis p of fractal terrain height fields is presented which, in contrast to revious techniques, features locally independent control of the f f frequencies composing the surface, and thus local control o ractal dimension and other statistical characteristics. The new f i technique, termed noise synthesis, is intermediate in difficulty o mplementation, between simple stochastic subdivision and s n Fourier filtering or generalized stochastic subdivision, and doe ot suffer the drawbacks of creases or periodicity. Varying the w local crossover scale of fractal character or the fractal dimension ith altitude or other functions yields more realistic first approxm imations to eroded landscapes. A simple physical erosion odel is then suggested which simulates hydraulic and thermal ...

Illustration using a coarse geometry clipmap (size n=31) View of the 216,000×93,600 U.S. dataset near Grand Canyon (n=255) Figure 1:Terrains rendered using geometry clipmaps, showing clipmap levels (size n×n) and transition regions (in blue on right). Rendering throughput has reached a level that enables a novel approach to level-of-detail (LOD) control in terrain rendering. We introduce the geometry clipmap, which caches the terrain in a set of nested regular grids centered about the viewer. The grids are stored as vertex buffers in fast video memory, and are incrementally refilled as the viewpoint moves. This simple framework provides visual continuity, uniform frame rate, complexity throttling, and graceful degradation. Moreover it allows two new exciting real-time functionalities: decompression and synthesis. Our main dataset is a 40GB height map of the United States. A compressed image pyramid reduces the size by a remarkable factor of 100, so that it fits entirely in memory. This compressed data also contributes normal maps for shading. As the viewer approaches the surface, we synthesize grid levels finer than the stored terrain using fractal noise displacement. Decompression, synthesis, and normal-map computations are incremental, thereby allowing interactive flight at 60 frames/sec.

Current technology provides a means to obtain sampled data that digitally describes three-dimensional surfaces and objects. Three-dimensional digitizing cameras can be used to obtain sampled data that maps the surface of three dimensional figures and models. Data obtained from such sources enable accurate renderings of the original surface. However, the digitizing process often provides much more data than is needed to accurately recreate the surface or object. In order to use such data in real-time visual simulators, a significant reduction in the data needed to accurately render the sampled surfaces is required. The techniques presented were developed to drastically reduce the number of data points required to depict an object without sacrificing the detail and accuracy inherent in the digitizing process. * Contact author. 1. INTRODUCTION As our technologically oriented civilization becomes increasingly more complex and sophisticated, the cost of training operators and technicians...

This paper describes the basis for techniques such as stochastic subdivision in the theory of random processes and estimation theory. The popular stochastic subdivision construction is then generalized to provide control of the autocorrelation and spectral properties of the synthesized random functions. The generalized construction is suitable for generating a variety of perceptually distinct high-quality random functions, including those with non-fractal spectra and directional or oscillatory characteristics. It is argued that a spectral modeling approach provides a more powerful and somewhat more intuitive perceptual characterization of random processes than does the fractal model. Synthetic textures and terrains are presented as a means of visually evaluating the generalized subdivision technique. Categories and Subject Descriptors: I.3.3 [Computer Graphics]: Picture/Image Generation; I.3.7 [Computer Graphics]: Three Dimensional Graphics and Realism -<F11.

A terrain is most often represented with a digital elevation map consisting of a set of sample points from the terrain surface. This paper presents a fast and practical algorithm to compute the horizon, or skyline, at all sample points of a terrain. The horizons are useful in a number of applications, including the rendering of self--shadowing displacement maps, visibility culling for faster flight simulation, and rendering of cartographic data. Experimental and theoretical results are presented which show that the algorithm is more accurate that previous algorithms and is faster than previous algorithms in terrains of more than 100,000 sample points. Keywords terrain, digital elevation map, horizon, skyline, visibility, shadows, rendering, GIS I. Introduction Terrains are most often represented with a digital elevation map which consists of a set of sample points from the terrain surface. The sample points are typically taken over a regular square grid and the terrain surface is in...

Abstract. Recently, a small number of papers have appeared in which the authors implement stochastic search algorithms, such as evolutionary computation, to generate game content, such as levels, rules and weapons. We propose a taxonomy of such approaches, centring on what sort of content is generated, how the content is represented, and how the quality of the content is evaluated. The relation between search-based and other types of procedural content generation is described, as are some of the main research challenges in this new field. The paper ends with some successful examples of this approach. 1

There are five fundamental concerns in the synthesis of realistic imagery of fractal landscapes: 1) convincing geometric models of terrain; 2) efficient algorithms for rendering those potentially-large terrain models; 3) atmospheric effects, or aerial perspective, to provide a sense of scale; 4) surface textures as models of natural phenomena such as clouds, water, rock strata, and so forth, to enhance visual detail in the image beyond what can be modelled geometrically; and 5) a global context in which to situate the scenes. Results in these five areas are presented, and some aspects of the development of computer graphics as a new process and medium for the fine arts are discussed. Heterogeneous terrain models are introduced, and preliminary experiments in simulating fluvial erosion are presented to provide fractal drainage network features. For imaging detailed terrain models we describe grid tracing, a time- and memory-efficient algorithm for ray tracing height fields. To obtain aerial perspective we develop geometric models of aerosol density distributions with efficient integration schemes for determining scattering and extinction, and an efficient Rayleigh scattering approximation. We also describe physically-based models of the rainbow and mirage. Proceduralism is an underlying theme of this work; this is the practice of abstracting models of complex form and behaviors into relatively terse algorithms, which are evaluated in a lazy fashion. Procedural textures are developed as models of natural phenomena such as mountains and clouds, culminating a procedural model of an Earth-like planet which in the future may be explored interactively in a virtual reality setting.

Texture as a surface representation is the subject of a wide body of computer vision and computer graphics literature. While texture is always associated with a form of repetition in the image, the repeating quantity may vary. The texture may be a color or albedo variation as in a checkerboard, a paisley print or zebra stripes. Very often in real-world scenes, texture is instead due to a surface height variation, e.g. pebbles, gravel, foliage and any rough surface. Such surfaces are referred to here as 3D textured surfaces. Standard texture recognition algorithms are not appropriate for 3D textured surfaces because the appearance of 3D textured surfaces changes in a complex manner with viewing direction, illumination direction and scale. Recent methods have been developed for recognition of 3D textured surfaces using a database of surfaces observed under varied imaging parameters. One of these methods is based on 3D textons obtained using K-means clustering of multiscale feature vectors. Another method uses eigen-analysis originally developed for appearance-based object recognition. In this work we develop a hybrid approach that employs both feature grouping and dimensionality reduction. The method is tested using the Columbia-Utrecht texture database (CUReT) and provides excellent recognition rates. The method is compared with existing recognition methods for 3D textured surfaces. A direct comparison is facilitated by empirical recognition rates from the same texture data set. The current method has key advantages over existing methods including requiring less apriori information on both the training and novel images. 1

In this paper we present an example-based system for terrain synthesis. In our approach, patches from sample terrain (represented by a height field) are used to generate new terrain. The synthesis is guided by a user-sketched feature map that specifies where terrain features occur in the resulting synthetic terrain. Our system emphasizes large-scale curvilinear features (ridges and valleys) because such features are the dominant visual elements in most terrain. Both the example height field and user’s sketch map are analyzed using a technique from the field of geomorphology. The system finds patches from the example data that match the features found in the user’s sketch. Patches are joined together using graph cuts and Poisson editing. The order in which patches are placed in the synthesized terrain is determined by breadth-first traversal of a feature tree and this generates improved results over standard rasterscan placement orders. Our technique supports user-controlled terrain synthesis in a wide variety of styles, based upon the visual richness of real-world terrain data.

Abstract—This paper presents a search-based method for generating maps for the popular real-time strategy (RTS) game StarCraft. We devise a representation of StarCraft maps suitable for evolutionary search, along with a set of fitness functions based on predicted entertainment value of those maps, as derived from theories of player experience. A multiobjective evolutionary algorithm is then used to evolve complete Star-Craft maps based on the representation and selected fitness functions. The output of this algorithm is a Pareto front approximation visualizing the tradeoff between the several fitness functions used, and where each point on the front represents a viable map. We argue that this method is useful for both automatic and machine-assisted map generation, and in particular that the Pareto fronts are excellent design support tools for human map designers. Keywords: Real-time strategy games, RTS, procedural content generation, evolutionary multiobjective optimization I.