Learning guidelines for automatic indoor scene design

作者：Liang, Yuan^*; Zhang, Song-Hai; Martin, Ralph Robert

来源：Multimedia Tools and Applications, 2019, 78(4): 5003-5023.

DOI：10.1007/s11042-018-6004-7

• Open-world application
• Automatic layout
• Probabilistic model
• Constrained optimization

In this work, we address a novel and practical problem of automatically generating a room design from given room function and basic geometry, which can be described as picking appropriate objects from a given database, and placing the objects with a group of pre-defined criteria. We formulate both object selection and placement problems as probabilistic models. The object selection is first formulated as a supervised generative model, to take room function into consideration. Object placement problem is then formulated as a Bayesian model, where parameters are inferred with Maximizing a Posteriori (MAP) objective. We solve the placement problem efficiently by introducing a solver based on Markov Chain Monte Carlo with a specific proposal function designed for the problem.

• 出版日期2019-2
• 单位清华大学