Abstract
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. By introducing a solver based on Markov Chain Monte Carlo (MCMC), the placement problem is solved efficiently.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Sketchup (2017). http://www.sketchup.com
Autodesk revit (2017). https://www.autodesk.com/products/revit-family/overview
Archicad (2017). http://www.graphisoft.com/archicad/
Fisher, M., Hanrahan, P.: Context-based search for 3d models. ACM Transactions on Graphics (TOG) 29(4), 182 (2010)
Savva, M., Chang, A.X., Agrawala, M.: Scenesuggest: Context-driven 3D scene design. arXiv preprint arXiv:1703.00061 (2017)
Fisher, M., Ritchie, D., Savva, M., Funkhouser, T., Hanrahan, P.: Example-based synthesis of 3D object arrangements. ACM Trans. Graphics (TOG) 30(4), 135 (2012)
Yu, L.F., Yeung, S.K., Terzopoulos, D.: The clutterpalette: an interactive tool for detailing indoor scenes. IEEE Trans. Visual Comput. Graphics 22(2), 1138–1148 (2016)
Xu, K., Chen, K., Fu, H., Sun, W.L., Hu, S.M.: Sketch2Scene: Sketch-based co-retrieval and co-placement of 3D models. ACM Trans. Graphics (TOG) 32(4), 123 (2013)
Chang, A.X., Eric, M., Savva, M., Manning, C.D.: SceneSeer: 3D scene design with natural language. arXiv preprint arXiv:1703.00050 (2017)
Merrell, P., Schkufza, E., Li, Z., Agrawala, M., Koltun, V.: Interactive furniture layout using interior design guidelines. ACM Trans. Graphics (TOG) 30(4), 87 (2011)
Yu, L.F., Yeung, S.K., Tang, C.K., Terzopoulos, D., Chan, T.F., Osher, S.J.: Make it home: automatic optimization of furniture arrangement. ACM Trans. Graphics (TOG) 30(4), 86 (2011)
Yeh, Y.T., Yang, L., Watson, M., Goodman, N.D., Hanrahan, P.: Synthesizing open worlds with constraints using locally annealed reversible jump mcmc. ACM Trans. Graphics (TOG) 31(4), 56 (2012)
Xiao, J., Owens, A., Torralba, A.: SUN3D: A database of big spaces reconstructed using SfM and object labels. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1625–1632 (2013)
The sims 4 (2017). https://www.thesims.com/
Papadimitriou, C.H., Tamaki, H., Raghavan, P., Vempala, S.: Latent semantic indexing: a probabilistic analysis. In: Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, pp. 159–168. ACM (1998)
Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3(Jan), 993–1022 (2003)
Ramage, D., Hall, D., Nallapati, R., Manning, C.D.: Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora. In: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, vol. 1, pp. 248–256. Association for Computational Linguistics (2009)
Liu, J.S.: The collapsed gibbs sampler in Bayesian computations with applications to a gene regulation problem. J. Am. Stat. Assoc. 89(427), 958–966 (1994)
Fruchterman, T.M., Reingold, E.M.: Graph drawing by force-directed placement. Softw. Pract. Experience 21(11), 1129–1164 (1991)
Fisher, M., Savva, M., Hanrahan, P.: Characterizing structural relationships in scenes using graph kernels. ACM Trans. Graphics (TOG) 30(4), 34 (2011)
Caliński, T., Harabasz, J.: A dendrite method for cluster analysis. Commun. Stat. Theory Methods 3(1), 1–27 (1974)
Liu, J.S., Liang, F., Wong, W.H.: The multiple-try method and local optimization in metropolis sampling. J. Am. Stat. Assoc. 95(449), 121–134 (2000)
Griffiths, D., Tenenbaum, M.: Hierarchical topic models and the nested chinese restaurant process. Adv. Neural Inform. Process. Syst. 16, 17 (2004)
Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp. 1097–1105 (2012)
Acknowledgments
This work was supported by Research Grant of Beijing Higher Institution Engineering Research Center and the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013/ under REA grant agreement n\(^{\circ }\) [612627].
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Liang, Y., Zhang, SH., Martin, R.R. (2017). Automatic Data-Driven Room Design Generation. In: Chang, J., Zhang, J., Magnenat Thalmann, N., Hu, SM., Tong, R., Wang, W. (eds) Next Generation Computer Animation Techniques. AniNex 2017. Lecture Notes in Computer Science(), vol 10582. Springer, Cham. https://doi.org/10.1007/978-3-319-69487-0_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-69487-0_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-69486-3
Online ISBN: 978-3-319-69487-0
eBook Packages: Computer ScienceComputer Science (R0)