Inverse Procedural Modeling by Automatic Generation of L‐systems

Stava, Ondrej; Beneš, Bedřich; Mĕch, Radomír; Aliaga, Daniel G.; Kristof, Peter

doi:10.1111/j.1467-8659.2009.01636.x

Cited by 112 publications

(68 citation statements)

References 29 publications

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“…Our work can also be viewed as a generalization of inverse procedural modeling [Aliaga et al 2007;Stava et al 2010;Bokeloh et al 2010], which aims to reconstruct a procedural representation from a given exemplar shape. Prior inverse procedural modeling techniques analyzed single example shapes in isolation.…”

Section: Related Workmentioning

confidence: 99%

A probabilistic model for component-based shape synthesis

et al. 2012

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Figure 1: Given 100 training airplanes (green), our probabilistic model synthesizes 1267 new airplanes (blue). AbstractWe present an approach to synthesizing shapes from complex domains, by identifying new plausible combinations of components from existing shapes. Our primary contribution is a new generative model of component-based shape structure. The model represents probabilistic relationships between properties of shape components, and relates them to learned underlying causes of structural variability within the domain. These causes are treated as latent variables, leading to a compact representation that can be effectively learned without supervision from a set of compatibly segmented shapes. We evaluate the model on a number of shape datasets with complex structural variability and demonstrate its application to amplification of shape databases and to interactive shape synthesis.

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Section: Related Workmentioning

confidence: 99%

A probabilistic model for component-based shape synthesis

et al. 2012

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“…While assuming no priors at all makes the task exceedingly difficult, several works have focused on exploiting a small set of domain-specific fundamental assumptions. Stava et al [9] proposed inverse procedural modeling of rules and parameter values for arbitrary 2D vector content (Figure 8). They assume terminal symbols are known and generate context-free rules for linear structures using L-systems.…”

Section: Inverse Procedures and Parameter Estimationmentioning

confidence: 99%

3D Design and Modeling of Smart Cities from a Computer Graphics Perspective

Aliaga

2012

ISRN Computer Graphics

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.Modeling cities, and urban spaces in general, is a daring task for computer graphics, computer vision, and visualization. Understanding, describing, and modeling the geometry and behavior of cities are significant challenges that ultimately benefit urban planning and simulation, mapping and visualization, emergency response, and entertainment. In this paper, we have collected and organized research which addresses this multidisciplinary challenge. In particular, we divide research in modeling cities and urban spaces into the areas of geometrical modeling and of behavioral modeling. The first area overlaps significantly with computer graphics and computer vision-our focus is on algorithms that produce intricate geometry quickly from a compact set of specifications (i.e., procedural modeling). The second area of behavioral modeling centers on understanding the underlying socioeconomic, meteorological, and resource consumption/waste production processes occurring within an urban space. Research in urban modeling, even from a computer graphics perspective, must tie the two areas of geometric and behavioral modeling together in order to ensure that useful 3D modeling techniques are developed and are placed within their needed context. In addition, we discuss the growing trend of inverse procedural modeling and some sample urban applications.

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“…Fig. 1) are not captured by grammars like the ones produced in recent work [Št'ava et al 2010;Bokeloh et al 2010]. While these papers showed promising results, we pursue a different approach to be able to handle challenging layouts.…”

Section: Introductionmentioning

confidence: 99%

“…An alternative strategy is to infer a grammar directly from a single input object, given in the form of images [Aliaga et al 2007;Müller et al 2007] or geometry [Št'ava et al 2010;Bokeloh et al 2010]. All these previous approaches have in common that they spend most of their effort on image and geometry analysis to understand the structure of the input, with symmetry detection being a major technical ingredient.…”

Section: Introductionmentioning

confidence: 99%

Procedural facade variations from a single layout

2013

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We introduce a framework to generate many variations of a facade design that look similar to a given facade layout. Starting from an input image, the facade is hierarchically segmented and labeled with a collection of manual and automatic tools. The user can then model constraints that should be maintained in any variation of the input facade design. Subsequently, facade variations are generated for different facade sizes, where multiple variations can be produced for a certain size. Computing such new facade variations has many unique challenges, and we propose a new algorithm based on interleaving heuristic search and quadratic programming. In contrast to most previous work, we focus on the generation of new design variations and not on the automatic analysis of the input's structure. Adding a modeling step with the user in the loop ensures that our results routinely are of high quality.

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Inverse Procedural Modeling by Automatic Generation of L‐systems

Abstract: We present an important step towards the solution of the problem of inverse procedural modeling by generating

Cited by 112 publications

References 29 publications

A probabilistic model for component-based shape synthesis

A probabilistic model for component-based shape synthesis

3D Design and Modeling of Smart Cities from a Computer Graphics Perspective

Procedural facade variations from a single layout

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