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Interactive sketching of urban procedural models
- Source :
- ACM Transactions on Graphics, ACM Transactions on Graphics, 2016, Proceedings of ACM SIGGRAPH 2016, 35 (4), pp.1-11. ⟨10.1145/2897824.2925951⟩, ACM Transactions on Graphics, Association for Computing Machinery, 2016, Proceedings of ACM SIGGRAPH 2016, 35 (4), pp.1-11. ⟨10.1145/2897824.2925951⟩
- Publication Year :
- 2016
- Publisher :
- Association for Computing Machinery (ACM), 2016.
-
Abstract
- International audience; 3D modeling remains a notoriously difficult task for novices despite significant research effort to provide intuitive and automated systems. We tackle this problem by combining the strengths of two popular domains: sketch-based modeling and procedural modeling. On the one hand, sketch-based modeling exploits our ability to draw but requires detailed, unambiguous drawings to achieve complex models. On the other hand, procedural modeling automates the creation of precise and detailed geometry but requires the tedious definition and parameterization of procedural models. Our system uses a collection of simple procedural grammars, called snippets, as building blocks to turn sketches into realistic 3D models. We use a machine learning approach to solve the inverse problem of finding the procedural model that best explains a user sketch. We use non-photorealistic rendering to generate artificial data for training con-volutional neural networks capable of quickly recognizing the procedural rule intended by a sketch and estimating its parameters. We integrate our algorithm in a coarse-to-fine urban modeling system that allows users to create rich buildings by successively sketching the building mass, roof, facades, windows, and ornaments. A user study shows that by using our approach non-expert users can generate complex buildings in just a few minutes.
- Subjects :
- Sketching
business.industry
Computer science
Deep learning
020207 software engineering
02 engineering and technology
3D modeling
Machine learning
computer.software_genre
Computer Graphics and Computer-Aided Design
Convolutional neural network
[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]
Sketch
Rendering (computer graphics)
Deep Learning
Rule-based machine translation
Shape modeling
0202 electrical engineering, electronic engineering, information engineering
Inverse Procedural Modeling
020201 artificial intelligence & image processing
Artificial intelligence
business
Procedural modeling
computer
Subjects
Details
- ISSN :
- 15577368 and 07300301
- Volume :
- 35
- Database :
- OpenAIRE
- Journal :
- ACM Transactions on Graphics
- Accession number :
- edsair.doi.dedup.....6037c8eecb9501549449aa0ea09fa839
- Full Text :
- https://doi.org/10.1145/2897824.2925951