Fast and Scalable Position-Based Layout Synthesis
| Autor: | Demetri Terzopoulos, Alan Litteneker, Tomer Weiss, Masaki Nakada, Lap-Fai Yu, Noah Duncan, Chenfanfu Jiang |
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| Rok vydání: | 2018 |
| Předmět: |
Scheme (programming language)
FOS: Computer and information sciences business.industry Computer science Probabilistic logic Process (computing) 020207 software engineering 02 engineering and technology Computer Graphics and Computer-Aided Design Automation Graphics (cs.GR) Visualization Computer Science - Graphics Computer engineering Signal Processing Scalability 0202 electrical engineering electronic engineering information engineering Computer Vision and Pattern Recognition business computer Software computer.programming_language |
| DOI: | 10.48550/arxiv.1809.10526 |
| Popis: | The arrangement of objects into a layout can be challenging for non-experts, as is affirmed by the existence of interior design professionals. Recent research into the automation of this task has yielded methods that can synthesize layouts of objects respecting aesthetic and functional constraints that are non-linear and competing. These methods usually adopt a stochastic optimization scheme, which samples from different layout configurations, a process that is slow and inefficient. We introduce an physics-motivated, continuous layout synthesis technique, which results in a significant gain in speed and is readily scalable. We demonstrate our method on a variety of examples and show that it achieves results similar to conventional layout synthesis based on Markov chain Monte Carlo (McMC) state-search, but is faster by at least an order of magnitude and can handle layouts of unprecedented size as well as tightly-packed layouts that can overwhelm McMC. Comment: 13 pages |
| Databáze: | OpenAIRE |
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