Journal of Computer Science and Technology

, Volume 22, Issue 6, pp 846–858 | Cite as

Simple Reconstruction of Tree Branches from a Single Range Image

  • Zhang-Lin ChengEmail author
  • Xiao-Peng Zhang
  • Bao-Quan Chen
Regular Paper


3D modeling of trees in real environments is a challenge in computer graphics and computer vision, since the geometric shape and topological structure of trees are more complex than conventional artificial objects. In this paper, we present a multi-process approach that is mainly performed in 2D space to faithfully construct a 3D model of the trunk and main branches of a real tree from a single range image. The range image is first segmented into patches by jump edge detection based on depth discontinuity. Coarse skeleton points and initial radii are then computed from the contour of each patch. Axis directions are estimated using cylinder fitting in the neighborhood of each coarse skeleton point. With the help of axis directions, skeleton nodes and corresponding radii are computed. Finally, these skeleton nodes are hierarchically connected, and improper radii are modified based on plant knowledge. 3D models generated from single range images of real trees demonstrate the effectiveness of our method. The main contributions of this paper are simple reconstruction by virtue of image storage order of single scan and skeleton computation based on axis directions.


cylinder fitting generalized circular cylinder skeleton tree branch modeling 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Supplementary material

11390_2007_Article_9095_ESM.pdf (82 kb)
(PDF 82 kb)


  1. [1]
    Phillippe de Reffye, Claude Edelin, Jean Françon et al. Plant models faithful to botanical structure and development. In Proc. 15th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’88, New York, USA, 1988, ACM Press, pp.151–158.CrossRefGoogle Scholar
  2. [2]
    Prusinkiewicz P, Aristid Lindenmayer. The Algorithmic Beauty of Plants. New York: Springer-Verlag New York, Inc., USA, 1990.zbMATHGoogle Scholar
  3. [3]
    Oliver Deussen, Bernd Lintermann. A modelling method and user interface for creating plants. In Proc. Conference on Graphics Interface’97, Toronto, Ont., Canada, 1997, Canadian Information Processing Society, pp.189–197.Google Scholar
  4. [4]
    Hui Xu, Nathan Gossett, Baoquan Chen. Knowledge-based modeling of laser-scanned trees. In Proc. SIGGRAPH’05: ACM SIGGRAPH 2005 Sketches, Los Angeles, California, USA, 2005, ACM Press, p.124.CrossRefGoogle Scholar
  5. [5]
    Long Quan, Ping Tan, Gang Zeng, Lu Yuan, Jingdong Wang, Sing Bing Kang. Image-based plant modeling. ACM Trans. Graph., 2006, 25(3): 599–604.CrossRefGoogle Scholar
  6. [6]
    Aschoff T, Thies M, Spiecker H. Describing forest stands using terrestrial laser-scanning. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXV(Part B5), ISPRS, 2004, pp.237–241.Google Scholar
  7. [7]
    Bienert A, Maas H G, Scheller S. Analysis of the information content of terrestrial laserscanner point clouds for the automatic determination of forest inventory parameters. In Proc. Workshop on 3D Remote Sensing in Forestry, 2006.Google Scholar
  8. [8]
    Thies M, Pfeifer N, Winterhalder D et al. Three-dimensional reconstruction of stems for assessment of taper, sweep and lean based on laser scanning of standing trees. Scandinavian J. Forest Research, 2004, 19(6): 571–581.CrossRefGoogle Scholar
  9. [9]
    Norbert Pfeifer, Ben Gorte, Daniel Winterhalder. Automatic reconstruction of single trees from terrestrial laser scanner data. In Proc. ISPRS Conf., Instanbul, Turkey, Int. Archives of Photogrammetry and Remote Sensing, Vol. XXXV, B5, 2004, pp.114–119.Google Scholar
  10. [10]
    David A Forsyth, Jean Ponce. Computer Vision: A Modern Approach. Prentice Hall, 2002.Google Scholar
  11. [11]
    Chin-Hung Teng, Yung-Sheng Chen, Wen-Hsing Hsu. Constructing a 3D trunk model from two images. Graph. Models, 2007, 69(1): 33–56.CrossRefGoogle Scholar
  12. [12]
    Maxime Lhuillier, Long Quan. A quasi-dense approach to surface reconstruction from uncalibrated images. IEEE Trans. Pattern Anal. Mach. Intell., 2005, 27(3): 418–433.CrossRefGoogle Scholar
  13. [13]
    Jules Bloomenthal. Modeling the mighty maple. In Proc. 12th Annual Conf. Computer Graphics and Interactive Techniques, SIGGRAPH’85, 1985, ACM Press, pp.305–311.Google Scholar
  14. [14]
    Przemyslaw Prusinkiewicz, Mark James, Radomír Mìch. Synthetic topiary. In Proc. 21st Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH’94, 1994, ACM Press, pp.351–358.Google Scholar
  15. [15]
    F Blaise, J F Barczi, M Jaeger, P Dinouard, P de Reffye. Simulation of the Growth of Plants — Modeling of Metamorphosis and Spatial Interactions in the Architecture and Development of Plants. Cyberworlds, Springer-Verlag, 2004, 1998, pp.81–109.Google Scholar
  16. [16]
    Bernd Lintermann, Oliver Deussen. Interactive modeling of plants. IEEE Comput. Graph. Appl., 1999, 19(1): pp.56–65.CrossRefGoogle Scholar
  17. [17]
    Makoto Okabe, Takeo Igarashi. 3D modeling of trees from freehand sketches. In Proc. ACM SIGGRAPH 2003 Sketches & Applications, SIGGRAPH’03, San Diego, California, USA, 2003, ACM Press, DVD-ROM.Google Scholar
  18. [18]
    Makoto Okabe, Shigeru Owada, Takeo Igarashi. Interactive design of botanical trees using freehand sketches and example-based editing. Computer Graphics Forum (Proc. of Eurographics’05), 2005, 24(3): 487–496.CrossRefGoogle Scholar
  19. [19]
    Ilya Shlyakhter, Max Rozenoer, Julie Dorsey et al. Reconstructing 3D tree models from instrumented photographs. IEEE Comput. Graph. Appl., 2001, 21(3): pp.53–61.CrossRefGoogle Scholar
  20. [20]
    Boris Neubert, Thomas Franken, Oliver Deussen. Approximate image-based tree-modeling using particle flows. In Proc. SIGGRAPH’07, San Diego, CA, USA, 2007.Google Scholar
  21. [21]
    Ping Tan, Gang Zeng, Jingdong Wang, Sing Bing Kang, Long Quan. Image-based tree modeling. In Proc. SIGGRAPH’07, San Diego, CA, USA, 2007.Google Scholar
  22. [22]
    Ben Gorte, Norbert Pfeifer. Structuring laser-scanned trees using 3D mathematical morphology. In Proc. ISPRS Conf., Instanbul, Turkey, Int. Archives of Photogrammetry and Remote Sensing, Vol. XXXV, B5, 2004, pp.929–933.Google Scholar
  23. [23]
    Vaughan Pratt. Direct least-squares fitting of algebraic surfaces. In Proc. the 14th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH’87, 1987, ACM Press, pp.145–152.Google Scholar
  24. [24]
    Gabor Lukács, Ralph Martin, Dave Marshall. Faithful least-squares fitting of spheres, cylinders, cones and tori for reliable segmentation. In Proc. the 5th European Conference on Computer Vision, ECCV’98, Vol. I, London, UK, 1998, Springer-Verlag, pp.671–686.Google Scholar
  25. [25]
    William H Press, Saul A Teukolsky, William T Vetterling, Brian P Flannery. Numerical Recipes in C: The Art of Scientific Computing, New York: Cambridge University Press, NY, USA, 1992.Google Scholar
  26. [26]
    Canny J. A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell., 1986, 8(6): 679–698.CrossRefGoogle Scholar
  27. [27]
    Jr D Dion, D Laurendeau, R Bergevin. Generalized cylinders extraction in a range image. In Proc. the International Conference on Recent Advances in 3-D Digital Imaging and Modeling, NRC’97, Washington DC, USA, 1997, IEEE Computer Society, pp.141–147.Google Scholar
  28. [28]
    Nevatia R, Binford T O. Description and recognition of curved objects. Artificial Intelligence, 1977, 8(1): 77–98.zbMATHCrossRefGoogle Scholar
  29. [29]
    Anders Adamson, Marc Alexa. Point-sampled cell complexes. ACM Trans. Graph., 2006, 25(3): 671–680.CrossRefGoogle Scholar
  30. [30]
    William T Reeves, David H Salesin, Robert L Cook. Rendering antialiased shadows with depth maps. In Proc. SIGGRAPH’87, 1987, ACM Press, pp.283–291.Google Scholar

Copyright information

© Science Press, Beijing, China and Springer Science + Business Media, LLC, USA 2007

Authors and Affiliations

  • Zhang-Lin Cheng
    • 1
    • 2
    Email author
  • Xiao-Peng Zhang
    • 1
    • 2
  • Bao-Quan Chen
    • 3
  1. 1.Sino-French Laboratory LIAMA, Institute of AutomationChinese Academy of SciencesBeijingChina
  2. 2.National Laboratory of Pattern Recognition, Institute of AutomationChinese Academy of SciencesBeijingChina
  3. 3.Digital Technology CenterUniversity of MinnesotaMinneapolisU.S.A.

Personalised recommendations