Feature based terrain generation using diffusion equation

Hnaidi, Houssam; Guérin, Éric; Akkouche, Samir; Peytavie, Adrien; Galin, Éric

doi:10.1111/j.1467-8659.2010.01806.x

Cited by 93 publications

(91 citation statements)

References 24 publications

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“…Despite a few attempts to force fractal generation to fit user-defined constraints [9], [10], the common problem of procedural terrain generators is their lack of direct control. In contrast other procedural methods model terrains from a set of 3D feature curves used to specify ridges or river networks [11], [12], with, however, little help from the system to improve realism. Génevaux et al [13] introduce a method that builds large terrains by combining river sections and terrains into a single geologically-based model.…”

Section: Related Workmentioning

confidence: 99%

Sculpting Mountains: Interactive Terrain Modeling Based on Subsurface Geology

Cordonnier

Cani

Beneš

et al. 2018

IEEE Trans. Visual. Comput. Graphics

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Abstract-Most mountain ranges are formed by the compression and folding of colliding tectonic plates. Subduction of one plate causes large-scale asymmetry while their layered composition (or stratigraphy) explains the multi-scale folded strata observed on real terrains. We introduce a novel interactive modeling technique to generate visually plausible, large scale terrains that capture these phenomena. Our method draws on both geological knowledge for consistency and on sculpting systems for user interaction. The user is provided hands-on control on the shape and motion of tectonic plates, represented using a new geologically-inspired model for the Earth crust. The model captures their volume preserving and complex folding behaviors under collision, causing mountains to grow. It generates a volumetric uplift map representing the growth rate of subsurface layers. Erosion and uplift movement are jointly simulated to generate the terrain. The stratigraphy allows us to render folded strata on eroded cliffs. We validated the usability of our sculpting interface through a user study, and compare the visual consistency of the earth crust model with geological simulation results and real terrains.

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Section: Related Workmentioning

confidence: 99%

Sculpting Mountains: Interactive Terrain Modeling Based on Subsurface Geology

Cordonnier

Cani

Beneš

et al. 2018

IEEE Trans. Visual. Comput. Graphics

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“…Procedural modeling methods exploit the observation that landform features repeat at different scales and define the elevation either as fractals [15,20] or by using a combination of scaled noise-based functions [17]. Several improvements were proposed to improve user control, such as terrains generated from feature curves [14], rivers [10] or a hierarchical construction tree representation [11]. Specifying generative rules that preserve the overall coherence of the scene is a difficult task, mainly because of the indirect control over the generation processes.…”

Section: Related Workmentioning

confidence: 99%

Coherent multi-layer landscape synthesis

et al. 2017

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We present an efficient method for generating coherent multi-layer landscapes. We use a dictionary built from exemplars to synthesize high-resolution fully-featured terrains from input low-resolution elevation data. Our example-based method consists in analyzing real world terrain examples and learning the procedural rules directly from these inputs. We take into account not only the elevation of the terrain, but also additional layers such as the slope, orientation, drainage area, the density and distribution of vegetation, and the soil type. By increasing the variety of terrain exemplars, our method allows the user to synthesize and control different types of landscapes and biomes, such as temperate or rain forests, arid deserts and mountains.

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“…This is the reason why several extensions have been proposed to improve artistic control using directional diffusion and blockers [3,4], or to produce a smoother color propagation [10]. Jeschke et al [13] also use diffusion curves to control the parameters of procedural textures, while Hnaidi et al [11] create height fields by diffusing height from curves that represent ridges and cliffs. Finally, Takayama et al [24] extend diffusion curves to diffusion surfaces to create volumetric models with 3D color gradients.…”

Section: Gradient Extremamentioning

confidence: 99%

Gradient Art: Creation and Vectorization

Barla

Bousseau²

2012

Computational Imaging and Vision

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There are two different categories of methods for producing vector gradients. One is mainly interested in converting existing photographs into dense vector representations. By vector it is meant that one can zoom infinitely inside images, and that control values do not have to lie onto a grid but must represent subtle color gradients found in input images. The other category is tailored to the creation of images from scratch, using a sparse set of vector primitives. In this case, we still have the infinite zoom property, but also an advanced model of how space should be filled in-between primitives, since there is no input photograph to rely on. These two categories are actually extreme cases, and seem to exclude each other: a dense representation is difficult to manipulate, especially when one wants to modify topology; a sparse representation is hardly adapted to photo vectorization, especially in the presence of texture. Very few methods lie in the middle, and the ones that do require user assistance. The challenge is worth the effort though: it would make converting an image into vector primitives easily amenable to stylization.

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Feature based terrain generation using diffusion equation

Cited by 93 publications

References 24 publications

Sculpting Mountains: Interactive Terrain Modeling Based on Subsurface Geology

Sculpting Mountains: Interactive Terrain Modeling Based on Subsurface Geology

Coherent multi-layer landscape synthesis

Gradient Art: Creation and Vectorization

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