“Learning shape placements by example” by Guerrero, Jeschke, Wimmer and Wonka

We present a method to learn and propagate shape placements in 2D polygonal scenes from a few examples provided by a user. The placement of a shape is modeled as an oriented bounding box. Simple geometric relationships between this bounding box and nearby scene polygons define a feature set for the placement. The feature sets of all example placements are then used to learn a probabilistic model over all possible placements and scenes. With this model, we can generate a new set of placements with similar geometric relationships in any given scene. We introduce extensions that enable propagation and generation of shapes in 3D scenes, as well as the application of a learned modeling session to large scenes without additional user interaction. These concepts allow us to generate complex scenes with thousands of objects with relatively little user interaction.

1. Bishop, C. M. 2006. Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag New York, Inc., Secaucus, NJ, USA. Google ScholarDigital Library
2. Bokeloh, M., Wand, M., Seidel, H.-P., and Koltun, V. 2012. An algebraic model for parameterized shape editing. ACM Trans. Graph. 31, 4 (July), 78:1–78:10. Google ScholarDigital Library
3. Boureau, Y.-L., Ponce, J., and Lecun, Y. 2010. A theoretical analysis of feature pooling in visual recognition. In 27th International Conference on Machine Learning, Haifa, Israel.Google Scholar
4. Chaudhuri, S., Kalogerakis, E., Guibas, L., and Koltun, V. 2011. Probabilistic reasoning for assembly-based 3d modeling. ACM Trans. Graph. 30, 4 (July), 35:1–35:10. Google ScholarDigital Library
5. Cui, Z., Zhang, H., and Lu, W. 2010. An improved smoothed l0-norm algorithm based on multiparameter approximation function. In Communication Technology (ICCT), 2010 12th IEEE International Conference on, 942–945.Google Scholar
6. Fisher, M., and Hanrahan, P. 2010. Context-based search for 3d models. ACM Trans. Graph. 29, 6 (Dec.), 182:1–182:10. Google ScholarDigital Library
7. Fisher, M., Savva, M., and Hanrahan, P. 2011. Characterizing structural relationships in scenes using graph kernels. ACM Trans. Graph. 30, 4 (July), 34:1–34:12. Google ScholarDigital Library
8. Fisher, M., Ritchie, D., Savva, M., Funkhouser, T., and Hanrahan, P. 2012. Example-based synthesis of 3d object arrangements. ACM Trans. Graph. 31, 6 (Nov.), 135:1–135:11. Google ScholarDigital Library
9. Funkhouser, T., Kazhdan, M., Shilane, P., Min, P., Kiefer, W., Tal, A., Rusinkiewicz, S., and Dobkin, D. 2004. Modeling by example. ACM Trans. Graph. 23, 3, 652–663. Google ScholarDigital Library
10. Gal, R., Sorkine, O., Mitra, N. J., and Cohen-Or, D. 2009. iWIRES: an analyze-and-edit approach to shape manipulation. ACM Trans. Graph. 28, 3 (July), 33:1–33:10. Google ScholarDigital Library
11. Guerrero, P., Jeschke, S., Wimmer, M., and Wonka, P. 2014. Edit propagation using geometric relationship functions. ACM Trans. Graph. 33, 2 (Apr.), 15:1–15:15. Google ScholarDigital Library
12. Kalogerakis, E., Chaudhuri, S., Koller, D., and Koltun, V. 2012. A probabilistic model for component-based shape synthesis. ACM Trans. Graph. 31, 4 (July), 55:1–55:11. Google ScholarDigital Library
13. Kitchen, L., and Rosenfeld, A. 1982. Gray-level corner detection. Pattern Recognition Letters 1, 2, 95–102. Google ScholarDigital Library
14. Kuhn, H. W. 1955. The hungarian method for the assignment problem. Naval Research Logistics Quarterly 2, 1–2, 83–97.Google ScholarCross Ref
15. Merrell, P., Schkufza, E., Li, Z., Agrawala, M., and Koltun, V. 2011. Interactive furniture layout using interior design guidelines. ACM Trans. Graph. 30, 4 (July), 87:1–87:10. Google ScholarDigital Library
16. Oxvig, C. S., Pedersen, P. S., Arildsen, T., and Larsen, T. 2012. Improving smoothed l0 norm in compressive sensing using adaptive parameter selection. CoRR abs/1210.4277.Google Scholar
17. XU, K., Stewart, J., and Fiume, E. 2002. Constraint-Based Automatic Placement for Scene Composition. In Graphics Interface, 25–34.Google Scholar
18. Yeh, Y.-T., Yang, L., Watson, M., Goodman, N. D., and Hanrahan, P. 2012. Synthesizing open worlds with constraints using locally annealed reversible jump mcmc. ACM TOG 31, 4 (July), 56:1–56:11. Google ScholarDigital Library
19. Yu, L.-F., Yeung, S.-K., Tang, C.-K., Terzopoulos, D., Chan, T. F., and Osher, S. J. 2011. Make it home: automatic optimization of furniture arrangement. ACM Trans. Graph. 30, 4 (July), 86:1–86:12. Google ScholarDigital Library
20. Zheng, Y., Fu, H., Cohen-Or, D., Au, O. K.-C., and Tai, C.-L. 2011. Component-wise controllers for structure-preserving shape manipulation. Computer Graphics Forum 30, 2, 563–572.Google ScholarCross Ref