Local Editing of Procedural Models

M. Lipp, M. Specht, C. Lau, Peter Wonka, P. Müller

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Procedural modeling is used across many industries for rapid 3D content creation. However, professional procedural tools often lack artistic control, requiring manual edits on baked results, diminishing the advantages of a procedural modeling pipeline. Previous approaches to enable local artistic control require special annotations of the procedural system and manual exploration of potential edit locations. Therefore, we propose a novel approach to discover meaningful and non-redundant good edit locations (GELs). We introduce a bottom-up algorithm for finding GELs directly from the attributes in procedural models, without special annotations. To make attribute edits at GELs persistent, we analyze their local spatial context and construct a meta-locator to uniquely specify their structure. Meta-locators are calculated independently per attribute, making them robust against changes in the procedural system. Functions on meta-locators enable intuitive and robust multi-selections. Finally, we introduce an algorithm to transfer meta-locators to a different procedural model. We show that our approach greatly simplifies the exploration of the local edit space, and we demonstrate its usefulness in a user study and multiple real-world examples.
Original languageEnglish (US)
Pages (from-to)13-25
Number of pages13
JournalComputer Graphics Forum
Issue number2
StatePublished - Jun 7 2019

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): URF/1/3426-01-01
Acknowledgements: We thank Matthias Buehler, Cyrill Oberhaensli and Yulia Leonova for assessing the methods presented in this paper. Special thanks go to Yulia for providing the images for Figure 7 (Context: Her work in the ‘Ideal Spaces Working Group’ for the Architecture Biennale 2018 exhibit in Venice: ‘Artificial Natures‘). We thank Stefan Lienhard for reviewing and providing suggestions for improving this paper. This work was supported in part by the KAUST Office of Sponsored Research (OSR) under Award URF/1/3426-01-01.


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