Procedural modeling

Summary

Procedural modeling is an umbrella term for a number of techniques in computer graphics to create 3D models and textures from sets of rules. L-Systems, fractals, and generative modeling are procedural modeling techniques since they apply algorithms for producing scenes. The set of rules may either be embedded into the algorithm, configurable by parameters, or the set of rules is separate from the evaluation engine. The output is called procedural content, which can be used in computer games, films, be uploaded to the internet, or the user may edit the content manually. Procedural models often exhibit database amplification, meaning that large scenes can be generated from a much smaller number of rules. If the employed algorithm produces the same output every time, the output need not be stored. Often, it suffices to start the algorithm with the same random seed to achieve this. Although all modeling techniques on a computer require algorithms to manage and store data at some point,

Official source

https://en.wikipedia.org/wiki/Procedural_modeling

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (2)

Related publications

Related people

Related units

Related concepts (7)

Related concepts

Related courses (4)

This course gives an introduction to the fundamental concepts and methods of the Digital Humanities, both from a theoretical and applied point of view. The course introduces the Digital Humanities circle of processing and interpretation, from data acquisition to new understandings.

The students study and apply fundamental concepts and algorithms of computer graphics for rendering, geometry synthesis, and animation. They design and implement their own interactive graphics programs.

This studio explores the meaningful generation of architectures by the use of artificial intelligence/deep learning and parametric tools and introduces the notion of the digital vernacular in architectural and urban design thinking.

Related courses

Related lectures (6)

Related lectures

Structure-aware Synthesis for Predictive Woven Fabric Appearance

Wenzel Alban Jakob, Shuang Zhao

Woven fabrics have a wide range of appearance determined by their small-scale 3D structure. Accurately modeling this structural detail can produce highly realistic renderings of fabrics and is critical for predictive rendering of fabric appearance. But building these yarnlevel volumetric models is challenging. Procedural techniques are manually intensive, and fail to capture the naturally arising irregularities which contribute significantly to the overall appearance of cloth. Techniques that acquire the detailed 3D structure of real fabric samples are constrained only to model the scanned samples and cannot represent different fabric designs. This paper presents a new approach to creating volumetric models of woven cloth, which starts with user-specified fabric designs and produces models that correctly capture the yarn-level structural details of cloth. We create a small database of volumetric exemplars by scanning fabric samples with simple weave structures. To build an output model, our method synthesizes a new volume by copying data from the exemplars at each yarn crossing to match a weave pattern that specifies the desired output structure. Our results demonstrate that our approach generalizes well to complex designs and can produce highly realistic results at both large and small scales. © 2012 ACM 0730-0301/2012/08-ART75.

ACM2012

Design Transformations for Rule-based Procedural Modeling

Cheryl Shaulya Lau, Stefan Lienhard, Mark Pauly

We introduce design transformations for rule-based procedural models, e.g., for buildings and plants. Given two or more procedural designs, each specified by a grammar, a design transformation combines elements of the existing designs to generate new designs. We introduce two technical components to enable design transformations. First, we extend the concept of discrete rule switching to rule merging, leading to a very large shape space for combining procedural models. Second, we propose an algorithm to jointly derive two or more grammars, called grammar co-derivation. We demonstrate two applications of our work: we show that our framework leads to a larger variety of models than previous work, and we show fine-grained transformation sequences between two procedural models.

Wiley2017