Attribute Grammars for Incremental Scene Graph Rendering

Harald Steinlechner, Georg Haaser, Stefan Maierhofer, Robert F. Tobler

2019

Abstract

Scene graphs, as found in many visualization systems are a well-established concept for modeling virtual scenes in computer graphics. State-of-the-art approaches typically issue appropriate draw commands while traversing the graph. Equipped with a functional programming mindset we take a different approach and utilize attribute grammars as a central concept for modeling the problem domain declaratively. Instead of issuing draw commands imperatively, we synthesize first class objects describing appropriate draw commands. In order to make this approach practical in the face of dynamic changes to the scene graph, we utilize incremental evaluation, and thereby avoid repeated evaluation of unchanged parts. Our application prototypically demonstrates how complex systems benefit from domain-specific languages, declarative problem solving and the implications thereof. Besides from being concise and expressive, our solution demonstrates a real-world use case of self-adjusting computation which elegantly extends scene graphs with well-defined reactive semantics and efficient, incremental execution.

Paper Citation

in Harvard Style

Steinlechner H., Haaser G., Maierhofer S. and Tobler R. (2019). Attribute Grammars for Incremental Scene Graph Rendering. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP; ISBN 978-989-758-354-4, SciTePress, pages 77-88. DOI: 10.5220/0007372800770088

in Bibtex Style

@conference{grapp19,
author={Harald Steinlechner and Georg Haaser and Stefan Maierhofer and Robert F. Tobler},
title={Attribute Grammars for Incremental Scene Graph Rendering},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP},
year={2019},
pages={77-88},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007372800770088},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP
TI - Attribute Grammars for Incremental Scene Graph Rendering
SN - 978-989-758-354-4
AU - Steinlechner H.
AU - Haaser G.
AU - Maierhofer S.
AU - Tobler R.
PY - 2019
SP - 77
EP - 88
DO - 10.5220/0007372800770088
PB - SciTePress