Sparse representation of terrains for procedural modeling

Guérin, Éric; Digne, Julie; Galin, Éric; Peytavie, Adrien

doi:10.1111/cgf.12821

Cited by 44 publications

(61 citation statements)

References 33 publications

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“…We have used an algorithm from [Guérin et al 2016] to add small-scale details to an existing terrain. We will refer to this method as terrain amplication as it considers the information in the terrain in order to amplify it.…”

Section: Related Workmentioning

confidence: 99%

Interactive example-based terrain authoring with conditional generative adversarial networks

et al. 2017

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Authoring virtual terrains presents a challenge and there is a strong need for authoring tools able to create realistic terrains with simple user-inputs and with high user control. We propose an example-based authoring pipeline that uses a set of terrain synthesizers dedicated to specic tasks. Each terrain synthesizer is a Conditional Generative Adversarial Network trained by using real-world terrains and their sketched counterparts. The training sets are built automatically with a view that the terrain synthesizers learn the generation from features that are easy to sketch. During the authoring process, the artist rst creates a rough sketch of the main terrain features, such as rivers, valleys and ridges, and the algorithm automatically synthesizes a terrain corresponding to the sketch using the learned features of the training samples. Moreover, an erosion synthesizer can also generate terrain evolution by erosion at a very low computational cost. Our framework allows for an easy terrain authoring and provides a high level of realism for a minimum sketch cost. We show various examples of terrain synthesis created by experienced as well as inexperienced users who are able to design a vast variety of complex terrains in a very short time.

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Section: Related Workmentioning

confidence: 99%

Interactive example-based terrain authoring with conditional generative adversarial networks

et al. 2017

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“…Another function-based approach [14] defines terrains as hierarchical construction trees, combining primitives with blending, carving, and warping operators. Guérin et al [15] introduce a procedural method to represent terrains as elevation functions defined as a sparse combination of primitives built from linear combinations of landform features stored in a dictionary. These features can be extracted either from real world datasets or procedural primitives, or from any combination of multiple terrain models.…”

Section: Related Workmentioning

confidence: 99%

Sculpting Mountains: Interactive Terrain Modeling Based on Subsurface Geology

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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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“…Some techniques have been successfully developed for generating vegetation [22]. Recently, the sparse representation of terrains [12] combined atoms whose characteristic landforms features can be extracted from exemplars and stored in an optimized dictionary.…”

Section: Related Workmentioning

confidence: 99%

“…The dictionary is created by analyzing multi-layer input exemplars and contains multi-layer atoms. Multi-layer terrain exemplars are first decomposed into partially overlapping patches as described in [12]. The multi-resolution dictionary is a set of two dictionaries denoted as (D, D), low-and high-resolution, with the same number of atoms and a one-to-one correspondence between their atoms.…”

Section: Dictionary Creationmentioning

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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Sparse representation of terrains for procedural modeling

Cited by 44 publications

References 33 publications

Interactive example-based terrain authoring with conditional generative adversarial networks

Interactive example-based terrain authoring with conditional generative adversarial networks

Sculpting Mountains: Interactive Terrain Modeling Based on Subsurface Geology

Coherent multi-layer landscape synthesis

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