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 fo...

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Detalles Bibliográficos
Autores: Argudo Medrano, Óscar|||0000-0003-3943-1839, Chica Calaf, Antonio|||0000-0003-0270-2332, Andújar Gran, Carlos Antonio|||0000-0002-8480-4713
Tipo de recurso: artículo
Fecha de publicación:2016
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/100361
Acceso en línea:https://hdl.handle.net/2117/100361
https://dx.doi.org/10.1016/j.cag.2016.03.005
Access Level:acceso abierto
Palabra clave:Computer drawing
Tree reconstruction
Tree rendering
Vegetation synthesis
IMAGE
PHOTOGRAPHS
DESIGN
MODELS
PLANTS
Infografia -- Models matemàtics
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Disseny assistit per ordinador
Descripción
Sumario: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.