Automatic Furniture Arrangement Using Greedy Cost Minimization
By Peter Kán and Hannes Kaufmann
Abstract
In this paper, we present a novel method for fast generation of furniture arrangements in interior scenes. Our method exploits the benefits of optimization-based approaches for global aesthetic rules and the advantages of procedural approaches for local arrangement of small objects. We generate the furniture arrangements for a given room in two steps: We first optimize the selection and arrangement of furniture objects in a room with respect to aesthetic and functional rules. The infinite trans-dimensional space of furniture layouts is rapidly explored by greedy cost minimization. In the second step, the procedural methods are locally applied in a stochastic fashion to generate important scene details. We demonstrate that our method achieves comparable results to a recent method for automatic interior design in terms of user preferences and that local procedural design enhances the result of optimization-based interior design. Additionally, our method is one order of magnitude faster than the compared method. Finally, the execution times of up to one second show that our method is suitable for generating large-scale indoor virtual environments during runtime.
Reference
P. Kán, H. Kaufmann: "Automatic Furniture Arrangement Using Greedy Cost Minimization"; in: "IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR)", IEEE Computer Society, 2018, 1 - 8.
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