Eric Guérin

Feature based terrain generation using diffusion equation

This paper presents a diffusion method for generating terrains from a set of parameterized curves that characterize the landform features such as ridge lines, riverbeds or cliffs. Our approach provides the user with an intuitive vector‐based feature‐oriented control over the terrain. Different types of constraints (such as elevation, slope angle and roughness) can be attached to the curves so as to define the shape of the terrain. The terrain is generated from the curve representation by using an efficient multigrid diffusion algorithm. The algorithm can be efficiently implemented on the GPU, which allows the user to interactively create a vast variety of landscapes.

Procedural Generation of Roads

In this paper, we propose an automatic method for generating roads based on a weighted anisotropic shortest path algorithm. Given an input scene, we automatically create a path connecting an initial and a final point. The trajectory of the road minimizes a cost function that takes into account the different parameters of the scene including the slope of the terrain, natural obstacles such as rivers, lakes, mountains and forests. The road is generated by excavating the terrain along the path and instantiating generic parameterized models.

Terrain generation using procedural models based on hydrology

We present a framework that allows quick and intuitive modeling of terrains using concepts inspired by hydrology. The terrain is generated from a simple initial sketch, and its generation is controlled by a few parameters. Our terrain representation is both analytic and continuous and can be rendered by using varying levels of detail. The terrain data are stored in a novel data structure: a construction tree whose internal nodes define a combination of operations, and whose leaves represent terrain features. The framework uses rivers as modeling elements, and it first creates a hierarchical drainage network that is represented as a geometric graph over a given input domain. The network is then analyzed to construct watersheds and to characterize the different types and trajectories of rivers. The terrain is finally generated by combining procedural terrain and river patches with blending and carving operators.

Authoring Hierarchical Road Networks

We present a procedural method for generating hierarchical road networks connecting cities, towns and villages over large terrains. Our approach relies on an original geometric graph generation algorithm based on a non‐Euclidean metric combined with a path merging algorithm that creates junctions between the different types of roads. Unlike previous work, our method allows high level user control by manipulating the density and the pattern of the network. The geometry of the highways, primary and secondary roads as well as the interchanges and intersections are automatically created from the graph structure by instantiating generic parameterized models.

Heat Transfer Simulation for Modeling Realistic Winter Sceneries

This paper presents a physically based method for simulating the heat transfers between the different environmental elements to synthesize realistic winter sceneries. We simulate the snow fall over the ground, as well as the conductive, convective and radiative thermal transfers using a finite volume method according to the variations of air and dew point temperatures, the amount of snow, cloud cover and day‐night cycles. Our approach takes into account phase changes such as snow melting into water or water freezing into ice.

Fractal coding of shapes based on a projected IFS model

This paper addresses the problem of approximation of natural complex shapes. Using MPEG-7 terminology, this problem can be considered as the search of a descriptor for a shape feature. This shape can be defined either as a frontier between image regions or a natural curve. For this purpose, an original descriptor which combines iterated function system (IFS) model and the notion of free form curves is proposed. A set of control points allows one to define the IFS model in a barycentric space. This generalization adds a real flexibility to fractal approximation techniques enriching the set of contractive operators which are candidate to model the self-similarity. This new descriptor named projected IFS model allows the reconstruction of a shape using a projection via the control points. It is adapted to the representation of both smooth shapes (man-made objects, body,..) and fractal shapes (mountain, cloud, tree,..). Results on synthetic shapes and a real mountain shape are presented.

A FRACTAL APPROXIMATION OF CURVES

This paper deals with the approximation of rough curves using a fractal model. The approximation criterion is based on a curve parametrization and the fractal model is a projected iterated function system (IFS) model. This model unifies the IFS model and a classical model used in computer graphics (free form representation with control points). To formulate the approximation problem, we introduce a family of curves based on our model. Then, the approximation problem has a nonlinear fitting formulation. We have tested this fractal approximation method on both smooth and rough synthetic curves. A shape extracted from a natural scene has also been approximated. The obtained results are very satisfying from both quantitative and visual point of view.

Transcriptional Induction of Stromelysin-3 in Mesodermal Cells Is Mediated by an Upstream CCAAT/Enhancer-binding Protein Element Associated with a DNase I-hypersensitive Site

Stromelysin-3 (ST3) is a matrix metalloproteinase whose synthesis is markedly increased in stromal fibroblasts of most invasive human carcinomas. In the present study, we have investigated the molecular mechanisms by which high levels of ST3 expression can be induced. In contrast to the early and transient induction of interstitial collagenase by 12-O-tetradecanoylphorbol-13-acetate (TPA), the fibroblastic induction of ST3 was found to be delayed and to require protein neosynthesis. We demonstrated that this induction is transcriptional and does not result from changes in RNA stability. By looking next to promoter regions accessible to DNase I upon gene induction, we have identified two distal elements and have characterized their role in the transcriptional regulation of ST3. The first one is a TPA-responsive element that controls the base-line ST3 promoter activity but is not required for its activation. We demonstrate that ST3 gene induction is actually mediated by the second element, a C/EBP-binding site, by showing: (i) that this element becomes accessible in cells induced to express ST3, (ii) that endogenous C/EBPβ binds to the ST3 promoter, and (iii) that this binding leads to ST3 transcriptional activation. Our study provides new insights into the regulation of ST3 and suggests an additional role for C/EBP transcription factors in tissue remodeling processes associated with this MMP.

Large Scale Terrain Generation from Tectonic Uplift and Fluvial Erosion

At large scale, landscapes result from the combination of two major processes: tectonics which generate the main relief through crust uplift, and weather which accounts for erosion. This paper presents the first method in computer graphics that combines uplift and hydraulic erosion to generate visually plausible terrains. Given a user‐painted uplift map, we generate a stream graph over the entire domain embedding elevation information and stream flow. Our approach relies on the stream power equation introduced in geology for hydraulic erosion. By combining crust uplift and stream power erosion we generate large realistic terrains at a low computational cost. Finally, we convert this graph into a digital elevation model by blending landform feature kernels whose parameters are derived from the information in the graph. Our method gives high‐level control over the large scale dendritic structures of the resulting river networks, watersheds, and mountains ridges.

Terrain Modelling from Feature Primitives

We introduce a compact hierarchical procedural model that combines feature‐based primitives to describe complex terrains with varying level of detail. Our model is inspired by skeletal implicit surfaces and defines the terrain elevation function by using a construction tree. Leaves represent terrain features and they are generic parametrized skeletal primitives, such as mountains, ridges, valleys, rivers, lakes or roads. Inner nodes combine the leaves and subtrees by carving, blending or warping operators. The elevation of the terrain at a given point is evaluated by traversing the tree and by combining the contributions of the primitives. The definition of the tree leaves and operators guarantees that the resulting elevation function is Lipschitz, which speeds up the sphere tracing used to render the terrain. Our model is compact and allows for the creation of large terrains with a high level o detail using a reduced set of primitives. We show the creation of different kinds of landscapes and demonstrate that our model allows to efficiently control the shape and distribution of landform features.