“Texture-lobes for tree modelling” by Livny, Pirk, Cheng, Yan, Deussen, et al. …

  • ©Yotam Livny, Soren Pirk, Zhanglin Cheng, Feilong Yan, Oliver Deussen, Daniel Cohen-Or, and Baoquan Chen




    Texture-lobes for tree modelling



    We present a lobe-based tree representation for modeling trees. The new representation is based on the observation that the tree’s foliage details can be abstracted into canonical geometry structures, termed lobe-textures. We introduce techniques to (i) approximate the geometry of given tree data and encode it into a lobe-based representation, (ii) decode the representation and synthesize a fully detailed tree model that visually resembles the input. The encoded tree serves as a light intermediate representation, which facilitates efficient storage and transmission of massive amounts of trees, e.g., from a server to clients for interactive applications in urban environments. The method is evaluated by both reconstructing laser scanned trees (given as point sets) as well as re-representing existing tree models (given as polygons).


    1. Agarwal, G., Belhumeur, P., Feiner, S., Jacobs, D., Kress, W., Ramamoorthi, R., Bourg, N., Dixit, N., Ling, H., Mahajan, D., et al. 2006. First steps toward an electronic field guide for plants. Taxon 55, 3, 597–610.Google ScholarCross Ref
    2. Anastacio, F., Sousa, M. C., Samavati, F., and Jorge, J. A. 2006. Modeling plant structures using concept sketches. In NPAR ’06, 105–113. Google Scholar
    3. Benes, B., Stava, O., Mech, R., and Miller, G. 2011. Guided procedural modeling. Comput. Graph. Forum 30, 2.Google ScholarCross Ref
    4. Bloomenthal, J. 1985. Modeling the mighty maple. SIGGRAPH ’85 19, 3, 305–311. Google Scholar
    5. Bucksch, A., and Lindenbergh, R. 2008. Campino — a skeletonization method for point cloud processing. ISPRS journal of photogrammetry and remote sensing 63, 1, 115–127.Google Scholar
    6. Bucksch, A., Lindenbergh, R., and Menenti, M. 2009. Skeltre – fast skeletonisation for imperfect point cloud data of botanic trees. In EG Workshop on 3D Object Retrieval, 13–27. Google Scholar
    7. Chen, X., Neubert, B., Xu, Y.-Q., Deussen, O., and Kang, S. B. 2008. Sketch-based tree modeling using markov random field. ACM Trans. Graph. 27, 5, 109–117. Google ScholarDigital Library
    8. Cheng, Z., Zhang, X., and Chen, B. 2007. Simple reconstruction of tree branches from a single range image. J. Comput. Sci. Technol. 22, 6, 846–858.Google ScholarCross Ref
    9. Cook, R. L., Halstead, J., Planck, M., and Ryu, D. 2007. Stochastic simplification of aggregate detail. ACM Trans. Graph. 26, 3, 79. Google ScholarDigital Library
    10. Côté, J.-F., Widlowski, J.-L., Fournier, R. A., and Verstraete, M. M. 2009. The structural and radiative consistency of three-dimensional tree reconstructions from terrestrial lidar. Remote Sensing of Environment 113, 5, 1067–1081.Google ScholarCross Ref
    11. Deussen, O., and Lintermann, B. 2005. Digital Design of Nature: Computer Generated Plants and Organics. SpringerVerlag New York, Inc. Google Scholar
    12. Deussen, O., Colditz, C., Stamminger, M., and Drettakis, G. 2002. Interactive visualization of complex plant ecosystems. In Visualization ’02, 219–226. Google ScholarDigital Library
    13. Edelsbrunner, H., and Mücke, E. P. 1994. Three-dimensional alpha shapes. ACM Trans. Graph. 13, 1, 43–72. Google ScholarDigital Library
    14. Efros, A. A., and Freeman, W. T. 2001. Image quilting for texture synthesis and transfer. In SIGGRAPH ’01, 341–346. Google Scholar
    15. Greene, N. 1989. Voxel space automata: modeling with stochastic growth processes in voxel space. SIGGRAPH ’89, 175–184. Google Scholar
    16. Honda, H. 1971. Description of the form of trees by the parameters of the tree-like body: Effects of the branching angle and the branch length on the shape of the tree-like body. Theoretical Biology 31, 331–338.Google ScholarCross Ref
    17. Ijiri, T., Owada, S., and Igarashi, T. 2006. The sketch l-system: Global control of tree modeling using free-form strokes. Smart Graphics, 138–146.Google Scholar
    18. Jaccard, P. 1913. Eine neue auffassung ber die ursachen des dickenwachstums der bŁume. Naturwiss. Z. fr. Landwirtschaft, 13, 321–360.Google Scholar
    19. Key, T., Warner, T., McGraw, J., and Fajvan, M. 2001. A Comparison of Multispectral and Multitemporal Information in High Spatial Resolution Imagery for Classification of Individual Tree Species in a Temperate Hardwood Forest. Remote Sensing of Environment 75, 1, 100–112.Google ScholarCross Ref
    20. Livny, Y., Yan, F., Olson, M., Chen, B., Zhang, H., and El-Sana, J. 2010. Automatic reconstruction of tree skeletal structures from point clouds. ACM Trans. Graph. 29, 6, 151. Google ScholarDigital Library
    21. Neubert, B., Franken, T., and Deussen, O. 2007. Approximate image-based tree-modeling using particle flows. ACM Trans. Graph. 26, 3, Article 71, 8 pages. Google ScholarDigital Library
    22. Okabe, M., Owada, S., and Igarashi, T. 2006. Interactive design of botanical trees using freehand sketches and example-based editing. Comput. Graph. Forum 24, 3, 487–496.Google ScholarCross Ref
    23. Palubicki, W., Horel, K., Longay, S., Runions, A., Lane, B., Měch, R., and Prusinkiewicz, P. 2009. Self-organizing tree models for image synthesis. ACM Trans. Graph. 28, 58. Google ScholarDigital Library
    24. Prusinkiewicz, P., and Lindenmayer, A. 1990. The algorithmic beauty of plants. Springer-Verlag New York, Inc. Google Scholar
    25. Reche-Martinez, A., Martin, I., and Drettakis, G. 2004. Volumetric reconstruction and interactive rendering of trees from photographs. ACM Trans. Graph. 23, 3, 720–727. Google ScholarDigital Library
    26. Reeves, W. T., and Blau, R. 1985. Approximate and probabilistic algorithms for shading and rendering structured particle systems. SIGGRAPH ’85 19, 3, 313–322. Google Scholar
    27. Runions, A., Lane, B., and Prusinkiewicz, P. 2007. Modeling trees with a space colonization algorithm. In Proceedings of Eurographics Workshop on Natural Phenomena 2007, 63–70. Google Scholar
    28. Shlyakhter, I., Rozenoer, M., Dorsey, J., and Teller, S. 2001. Reconstructing 3d tree models from instrumented photographs. IEEE Comput. Graph. 21, 3, 53–61. Google ScholarCross Ref
    29. Stava, O., Benes, B., Mech, R., Aliaga, D., and Kristof, P. 2010. Inverse procedural modeling by automatic generation of l-systems. Comput. Graph. Forum 29, 2.Google Scholar
    30. Talton, J., Lou, Y., Lesser, S., Duke, J., Měch, R., and Koltun, V. 2011. Metropolis procedural modeling. ACM Trans. Graphics 30, 2. Google ScholarDigital Library
    31. Tan, P., Zeng, G., Wang, J., Kang, S. B., and Quan, L. 2007. Image-based tree modeling. ACM Trans. Graph. 26, 3. Google ScholarDigital Library
    32. Tan, P., Fang, T., Xiao, J., Zhao, P., and Quan, L. 2008. Single image tree modeling. ACM Trans. Graph. 27, 5, 108. Google ScholarDigital Library
    33. Torralba, A., Murphy, K. P., and Freeman, W. T. 2007. Sharing visual features for multiclass and multiview object detection. IEEE Trans. Pattern Anal. Mach. Intell. 29, 854–869. Google ScholarDigital Library
    34. Verroust, A., and Lazarus, F. 1999. Extracting skeletal curves from 3D scattered data. In Proc. IEEE Conf. on Shape Modeling and Applications, 194–201. Google ScholarDigital Library
    35. Wither, J., Boudon, F., Cani, M.-P., and Godin, C. 2009. Structure from silhouettes: a new paradigm for fast sketch-based design of trees. Comput. Graph. Forum 28, 2, 541–550.Google ScholarCross Ref
    36. Xu, H., Gossett, N., and Chen, B. 2007. Knowledge and heuristic-based modeling of laser-scanned trees. ACM Trans. Graph. 26, 4, Article 19, 13 pages. Google ScholarDigital Library
    37. Zhu, C., Zhang, X., Huand, B., and Jaeger, M. 2008. Reconstruction of tree crown shape from scanned data. Technologies for E-Learning and Digital Entertainment, 745–756. Google Scholar

ACM Digital Library Publication: