Single-picture reconstruction and rendering of trees for plausible vegetation synthesis

State-of-the-art approaches for tree reconstruction either put limiting constraints on the input side (requiring multiple photographs, a scanned point cloud or intensive user input) or provide a representation only suitable for front views of the tree. In this paper we present a complete pipeline for synthesizing and rendering detailed trees from a single photograph with minimal user effort. Since the overall shape and appearance of each tree is recovered from a single photograph of the tree crown, artists can benefit from georeferenced images to populate landscapes with native tree species. A key element of our approach is a compact representation of dense tree crowns through a radial distance map. Our first contribution is an automatic algorithm for generating such representations from a single exemplar image of a tree. We create a rough estimate of the crown shape by solving a thin-plate energy minimization problem, and then add detail through a simplified shape-from-shading approach. The use of seamless texture synthesis results in an image-based representation that can be rendered from arbitrary view directions at different levels of detail. Distant trees benefit from an output-sensitive algorithm inspired on relief mapping. For close-up trees we use a billboard cloud where leaflets are distributed inside the crown shape through a space colonization algorithm. In both cases our representation ensures efficient preservation of the crown shape. Major benefits of our approach include: it recovers the overall shape from a single tree image, involves no tree modeling knowledge and minimal authoring effort, and the associated image-based representation is easy to compress and thus suitable for network streaming.Peer ReviewedPostprint (author's final draft

Scalable Realtime Rendering and Interaction with Digital Surface Models of Landscapes and Cities

Interactive, realistic rendering of landscapes and cities differs substantially from classical terrain rendering. Due to the sheer size and detail of the data which need to be processed, realtime rendering (i.e. more than 25 images per second) is only feasible with level of detail (LOD) models. Even the design and implementation of efficient, automatic LOD generation is ambitious for such out-of-core datasets considering the large number of scales that are covered in a single view and the necessity to maintain screen-space accuracy for realistic representation. Moreover, users want to interact with the model based on semantic information which needs to be linked to the LOD model. In this thesis I present LOD schemes for the efficient rendering of 2.5d digital surface models (DSMs) and 3d point-clouds, a method for the automatic derivation of city models from raw DSMs, and an approach allowing semantic interaction with complex LOD models. The hierarchical LOD model for digital surface models is based on a quadtree of precomputed, simplified triangle mesh approximations. The rendering of the proposed model is proved to allow real-time rendering of very large and complex models with pixel-accurate details. Moreover, the necessary preprocessing is scalable and fast. For 3d point clouds, I introduce an LOD scheme based on an octree of hybrid plane-polygon representations. For each LOD, the algorithm detects planar regions in an adequately subsampled point cloud and models them as textured rectangles. The rendering of the resulting hybrid model is an order of magnitude faster than comparable point-based LOD schemes. To automatically derive a city model from a DSM, I propose a constrained mesh simplification. Apart from the geometric distance between simplified and original model, it evaluates constraints based on detected planar structures and their mutual topological relations. The resulting models are much less complex than the original DSM but still represent the characteristic building structures faithfully. Finally, I present a method to combine semantic information with complex geometric models. My approach links the semantic entities to the geometric entities on-the-fly via coarser proxy geometries which carry the semantic information. Thus, semantic information can be layered on top of complex LOD models without an explicit attribution step. All findings are supported by experimental results which demonstrate the practical applicability and efficiency of the methods

Procedural Generation and Rendering of Realistic, Navigable Forest Environments: An Open-Source Tool

Simulation of forest environments has applications from entertainment and art creation to commercial and scientific modelling. Due to the unique features and lighting in forests, a forest-specific simulator is desirable, however many current forest simulators are proprietary or highly tailored to a particular application. Here we review several areas of procedural generation and rendering specific to forest generation, and utilise this to create a generalised, open-source tool for generating and rendering interactive, realistic forest scenes. The system uses specialised L-systems to generate trees which are distributed using an ecosystem simulation algorithm. The resulting scene is rendered using a deferred rendering pipeline, a Blinn-Phong lighting model with real-time leaf transparency and post-processing lighting effects. The result is a system that achieves a balance between high natural realism and visual appeal, suitable for tasks including training computer vision algorithms for autonomous robots and visual media generation.Comment: 14 pages, 11 figures. Submitted to Computer Graphics Forum (CGF). The application and supporting configuration files can be found at https://github.com/callumnewlands/ForestGenerato

Image-based tree variations

The automatic generation of realistic vegetation closely reproducing the appearance of specific plant species is still a challenging topic in computer graphics. In this paper, we present a new approach to generate new tree models from a small collection of frontal RGBA images of trees. The new models are represented either as single billboards (suitable for still image generation in areas such as architecture rendering) or as billboard clouds (providing parallax effects in interactive applications). Key ingredients of our method include the synthesis of new contours through convex combinations of exemplar countours, the automatic segmentation into crown/trunk classes and the transfer of RGBA colour from the exemplar images to the synthetic target. We also describe a fully automatic approach to convert a single tree image into a billboard cloud by extracting superpixels and distributing them inside a silhouette-defined 3D volume. Our algorithm allows for the automatic generation of an arbitrary number of tree variations from minimal input, and thus provides a fast solution to add vegetation variety in outdoor scenes.Peer ReviewedPostprint (author's final draft

View-dependent Object Simplification and its Application in the case of Billboard Clouds

Slightly modified from the original versionNational audienceIn this Master thesis we will present a new approach to simplify a model representation based on a supplementary knowledge of a region in which the observer is allowed to move, the so-called view cell. The simplified representation should be faster to render, without loosing the similarity to the original objects. To assure this we will present our main contribution, a new error bounding method, which to our best knowledge, allows for the first time to restrain the error of a representation for a given view cell. In particular, a lot of common assumptions that were widely accepted are proven to be inexact. We will show several properties for the 3D case and solve a particular case, as well as a numerical solution for points in 3D. For the 2D case we were able to obtain an exact solution which allows our method to be applied on 2.5 dimensional scenes. Our error bounding method is then used in the context of Billboard Clouds [DDSD03]. Still, our result is more general and thus not at all restricted to this particular usage. The view-dependent Billboard Clouds that we will introduce in this master thesis have several advantages. The error of the representation can be bound and the simplification is very successful; to mention one example a 4480 triangle scene has been simplified to approximately 40 billboards (80 triangles) with a ¼ 5% representation error1, for a centered view cell inside of the scene with a size approximately 1/10 of the bounding diagonal. Most algorithms add ad-hoc criteria to preserve silhouettes, our algorithm preserves them automatically. Other advantages of our method are that it works for any kind of triangulated input and that it is easy to use; only two parameters are needed (simplification error and texture quality). It is completely independent of the view frustum that is used for the observer, which is not very common, as most image based view-dependent simplification methods need a fixed view frustum. Also our method does not share a common problem with most other view cell approaches, where the representation becomes worse when the observer approaches the border of the view cell. The construction of view-dependent Billboard Clouds is mostly based on the original Billboard Cloud approach [DDSD03], but some slight improvements were made with respect to the original algorithm

Space Carving multi-view video plus depth sequences for representation and transmission of 3DTV and FTV contents

La vidéo 3D a suscité un intérêt croissant durant ces dernières années. Grâce au développement récent des écrans stéréoscopiques et auto-stéréoscopiques, la vidéo 3D fournit une sensation réaliste de profondeur à l'utilisateur et une navigation virtuelle autour de la scène observée. Cependant de nombreux défis techniques existent encore. Ces défis peuvent être liés à l'acquisition de la scène et à sa représentation d'une part ou à la transmission des données d'autre part. Dans le contexte de la représentation de scènes naturelles, de nombreux efforts ont été fournis afin de surmonter ces difficultés. Les méthodes proposées dans la littérature peuvent être basées image, géométrie ou faire appel à des représentations combinant image et géométrie. L'approche adoptée dans cette thèse consiste en une méthode hybride s'appuyant sur l'utilisation des séquences multi-vues plus profondeur MVD (Multi-view Video plus Depth) afin de conserver le photo-réalisme de la scène observée, combinée avec un modèle géométrique, à base de maillage triangulaire, renforçant ainsi la compacité de la représentation. Nous supposons que les cartes de profondeur des données MVD fournies sont fiables et que les caméras utilisées durant l'acquisition sont calibrées, les paramètres caméras sont donc connus, mais les images correspondantes ne sont pas nécessairement rectifiées. Nous considérerons ainsi le cas général où les caméras peuvent être parallèles ou convergentes. Les contributions de cette thèse sont les suivantes. D'abord, un schéma volumétrique dédié à la fusion des cartes de profondeur en une surface maillée est proposé. Ensuite, un nouveau schéma de plaquage de texture multi-vues est proposé. Finalement, nous abordons à l'issue ce ces deux étapes de modélisation, la transmission proprement dite et comparons les performances de notre schéma de modélisation avec un schéma basé sur le standard MPEG-MVC, état de l'art dans la compression de vidéos multi-vues.3D videos have witnessed a growing interest in the last few years. Due to the recent development ofstereoscopic and auto-stereoscopic displays, 3D videos provide a realistic depth perception to the user and allows a virtual navigation around the scene. Nevertheless, several technical challenges are still remaining. Such challenges are either related to scene acquisition and representation on the one hand or to data transmission on the other hand. In the context of natural scene representation, research activities have been strengthened worldwide in order to handle these issues. The proposed methods for scene representation can be image-based, geometry based or methods combining both image and geometry. In this thesis, we take advantage of image based representations, thanks to the use of Multi-view Video plus Depth representation, in order to preserve the photorealism of the observed scene, and geometric based representations in order to enforce the compactness ofthe proposed scene representation. We assume the provided depth maps to be reliable.Besides, the considered cameras are calibrated so that the cameras parameters are known but thecorresponding images are not necessarily rectified. We consider, therefore, the general framework where cameras can be either convergent or parallel. The contributions of this thesis are the following. First, a new volumetric framework is proposed in order to mergethe input depth maps into a single and compact surface mesh. Second, a new algorithm for multi-texturing the surface mesh is proposed. Finally, we address the transmission issue and compare the performance of the proposed modeling scheme with the current standard MPEG-MVC, that is the state of the art of multi-view video compression.RENNES-INSA (352382210) / SudocSudocFranceF

Towards Predictive Rendering in Virtual Reality

The strive for generating predictive images, i.e., images representing radiometrically correct renditions of reality, has been a longstanding problem in computer graphics. The exactness of such images is extremely important for Virtual Reality applications like Virtual Prototyping, where users need to make decisions impacting large investments based on the simulated images. Unfortunately, generation of predictive imagery is still an unsolved problem due to manifold reasons, especially if real-time restrictions apply. First, existing scenes used for rendering are not modeled accurately enough to create predictive images. Second, even with huge computational efforts existing rendering algorithms are not able to produce radiometrically correct images. Third, current display devices need to convert rendered images into some low-dimensional color space, which prohibits display of radiometrically correct images. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented and their limitations are pointed out. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering. A special focus of this thesis lays on real-time generation of predictive images using bidirectional texture functions (BTFs), i.e., very accurate representations for spatially varying surface materials. The techniques proposed by this thesis enable efficient handling of BTFs by compressing the huge amount of data contained in this material representation, applying them to geometric surfaces using texture and BTF synthesis techniques, and rendering BTF covered objects in real-time. Further approaches proposed in this thesis target inclusion of real-time global illumination effects or more efficient rendering using novel level-of-detail representations for geometric objects. Finally, this thesis assesses the rendering quality achievable with BTF materials, indicating a significant increase in realism but also confirming the remainder of problems to be solved to achieve truly predictive image generation

Visualization of Industrial Structures with Implicit GPU Primitives

International audienceWe present a method to interactively visualize large industrial models by replacing most triangles with implicit GPU primitives: cylinders, cone and torus slices. After a reverse-engineering process that recovers these primitives from triangle meshes, we encode their implicit parameters in a texture that is sent to the GPU. In rendering time, the implicit primitives are visualized seamlessly with other triangles in the scene. The method was tested on two massive industrial models, achieving better performance and image quality while reducing memory use