Advertisement

A Method for Detecting Flower Collision Based on Spherical Projection

  • Tingrong Cao
  • Ling Lu
  • Wenli Wang
  • Lihua Li
  • Lei Wang
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 875)

Abstract

In this paper, a method for detecting and mapping the petals of plant petals is presented. Firstly, the parametric equations are used to represent the initial state of the petals surface. The three - dimensional Cartesian coordinates of each point in the petals are projected onto the spherical coordinates respectively, The discrete values of the projection of the petals are converted to the two-dimensional coordinate plane. Secondly, multiple buffers are used to record the result of each petals projection and the distance of the petals from the origin of the spherical coordinates. According to the value of each buffer, it is determined whether the current petal collides with others, the collides result can be determined the range of collision. Finally, the current petals are deformed or moved to avoid collided with others. Through the collision test between the petals in the process of flower generation, it shows that the detection effect is good.

Keywords

Collision Projecting Plant flower Deforming 

Notes

Acknowledgment

This work was funded by two Natural Science Foundation of China (61561003 and 61761003)

References

  1. 1.
    Wu, M., Yu, Y., Zhou, J.: An octree algorithm for collision detection using space partition. Chin. J. Comput. 20(9), 849–854 (1997)Google Scholar
  2. 2.
    Redon, S., Kim, Y.J., Lin, M.C., et al.: Fast continuous collision detection for articulated models. In: Proceeding Soft the 9th ACM Symposium on Solid Modeling and Applications Airela-Ville Euro graphics Association Press, pp. 145–156 (2004)Google Scholar
  3. 3.
    Gottschalk, S., Lin, M.C., Manocha, D.: OBBTree.: a hierarchical structure for rapid interference detection. In: Computer Graphics Proceedings Annual Conference Series ACM SIGGRAPH, pp. 171–180 (1996)Google Scholar
  4. 4.
    Klosowski, J.T., Held, M., Mitchell, J.S.B., et al.: Efficient collision detection using bounding volume hierarchies of k-DOPS. IEEE Trans. Vis. Comput. Graph. 4(1), 21–36 (1998)CrossRefGoogle Scholar
  5. 5.
    Larse, E., Gottschalk, S., Lin, M.C., et al.: Fast proximity queries with swept sphere volumes. North Carolina University of North Carolina Department of Computer Science (1999)Google Scholar
  6. 6.
    Bradshaw, G., O Sullivan, C.: Sphere-tree construction using dynamic media lax is approximation. In: Proceeding Soft the ACM SIGGRAPH Euro Graphics Symposium on Computer Animation, pp. 33–40 (2002)Google Scholar
  7. 7.
    Corrales, J.A., Candelas, F.A., Torres, F.: Safe human-robot interaction based on dynamic sphere-swept line bounding volumes. Robot. Comput.-Integr. Manuf. 27(1), 177–185 (2011)CrossRefGoogle Scholar
  8. 8.
    Memory-optimized bounding-volume hierarchies. http://www.codecorner.com/Opcod. Accessed 28 Sept 2013
  9. 9.
    Chen, X., Yong, J., Zheng, G., et al.: Computing minimum distance between two Bezier curves/surfaces. Comput. Aided Geom. Des. 25(3), 677–684 (2006)Google Scholar
  10. 10.
    Chena, X., Yong, J., Zheng, G., et al.: Computing minimum distance between two implicit algebraic surfaces. Comput. Aided Geomet. Des. 38(4), 1053–1061 (2006)CrossRefGoogle Scholar
  11. 11.
    Lee, K., Seong, J.-K., Kim, K.-J., et al.: Minimum distance between two sphere-swept surfaces. Comput. Aided Geomet. Des. 39(1), 452–459 (2007)CrossRefGoogle Scholar
  12. 12.
    Turbull, C., Cameron, S.: Computing distances between NURBS-defined convex objects. In: Proceeding of IEEE International Conference on Robotics and Automation, pp. 236–239 (2008)Google Scholar
  13. 13.
    Ma, Y., Tu, C., Wang, W.: Distance computation for canal surfaces using cone-sphere bounding volumes. Comput. Aided Geomet. Des. 29(3), 255–264 (2012)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Rossignac, J., Megahed, A., Schneider, B.O.: Interactive inspection of solids: cross-section and interferences. In: Computer Graphics Proceedings, Annual Conference Series, ACM SIGGRAPH, pp. 353–360 (1992)Google Scholar
  15. 15.
    Rossignac, J., Megahed, A., Schneider, B.O.: Interactive inspection of solids: cross-section and interferences. Comput. Graph. 10(4), 181–192 (1999)Google Scholar
  16. 16.
    Baciu, G., Wong, S.K.W., Sun, H.: RECODE.: an image-based collision detection algorithm. J. Vis. Comput. Anim. 10(4), 181–192 (1999)CrossRefGoogle Scholar
  17. 17.
    Hoff III, K.E., Zaferakis, A., Lin, M., Manocha, D.: Fast and simple 2D geometric proximity queries using graphics hardware. In: Proceedings of ACM Symposium on Interactive 3D Graphics, pp. 145–148 (2001)Google Scholar
  18. 18.
    Bridson, R., Fedkiw, R., Anderson, J.: Robust treatment of collisions, contact and friction for cloth animation. ACM Trans. Graph. (TOG) 21(3), 594–603 (2002)CrossRefGoogle Scholar
  19. 19.
    Raghupathi, L., Grisoni, L., Faure, F., et al.: An intestinal surgery simulator: real-time collision processing and visualization. IEEE Trans. Vis. Comput. Graph. 10(6), 708–718 (2004)CrossRefGoogle Scholar
  20. 20.
    Tang, Y., Yang, S., Lu, M., et al.: Adaptive ellipsoidal surround box improvement of fabric collision detection method. Comput. Aided Des. Graph. J. 25(10), 1589–1596 (2013)Google Scholar
  21. 21.
    Zhang, X.Y., Kim, Y.: Interactive collision detection for deformable models using streaming ABBs. IEEE Trans. Vis. Comput. Graph. 13(2), 318–329 (2007)CrossRefGoogle Scholar
  22. 22.
    Tang, M., Manocha, D., Lin, J., et al.: Collision-streams: fast GPU based collision detection for deformable models. In: Symposium on Interactive 3D Graphics and Games, pp. 63–70. ACM, New York (2011)Google Scholar
  23. 23.
    Zhou, Q., Liu, Y., Cheng, T.: A continuous collision detection algorithm for large soft bodies. J. Chin. Image Graph. 21(7), 91–912 (2016)Google Scholar
  24. 24.
    Lu, L.: Study of flower color simulation. J. Syst. Simul. 24(9), 1892–1895 (2012)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Tingrong Cao
    • 1
  • Ling Lu
    • 1
    • 2
  • Wenli Wang
    • 1
  • Lihua Li
    • 2
  • Lei Wang
    • 2
  1. 1.Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data TechnologyEast China University of TechnologyNanchangChina
  2. 2.Jiangxi Engineering Research Center of Nuclear Geoscience Data Science and SystemEast China University of TechnologyNanchangChina

Personalised recommendations