Local Editing of Procedural Models

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

Local Editing of Procedural Models

Embargo End Date

2020-06-07

Type

Article

Authors

Lau, C.

KAUST Department

Computer Science
Computer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Visual Computing Center
Visual Computing Center (VCC)

KAUST Grant Number

URF/1/3426-01-01

Online Publication Date

2019-06-07

Print Publication Date

2019-05

Date

2019-06-07

Abstract

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.

Citation

Lipp, M., Specht, M., Lau, C., Wonka, P., & Müller, P. (2019). Local Editing of Procedural Models. Computer Graphics Forum, 38(2), 13–25. doi:10.1111/cgf.13615

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.