Skip to main content
Springer Nature Link
Log in

AB3D: action-based 3D descriptor for shape analysis

  • Original Article
  • Published:
The Visual Computer Aims and scope Submit manuscript

An Erratum to this article was published on 15 July 2014

Abstract

High-level geometry processing has been a hot topic in graphics community. The functionality analysis of 3D models is an essential issue in this area. Existing 3D models often exhibit both large intra-class and inter-class variations in shape geometry and topology, making the consistent analysis of functionality challenging. Traditional 3D shape analysis methods which rely on geometric shape descriptors can not obtain satisfying results on these 3D models. We develop a new 3D shape descriptor based on the interactions between 3D models and virtual human actions, which is called Action-Based 3D Descriptor (AB3D). Due to the implied semantic meanings of virtual human actions, we obtain encouraging results on consistent segmentation based on AB3D. Finally, we present a method for recognition and reconstruction of scanned 3D indoor scenes using our AB3D. Experiments show that AB3D is a promising shape descriptor toward functionality analysis of 3D shapes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Mitra, N.J., Wand, M., Zhang, H., Cohen-Or, D., Bokeloh, M.: Structure-aware shape processing, In EUROGRAPHICS State-of-the-art Report (2013)

  2. Chen, X., Golovinskiy, A., Funkhouser, T.: A benchmark for 3D mesh segmentation. ACM Trans. Graph. 28(3), 73 (2009)

    Article  Google Scholar 

  3. Golovinskiy, A., Funkhouser, T.: Consistent segmentation of 3D models. Comput. Graph. 33(3), 262–269 (2009)

    Article  Google Scholar 

  4. Xu, K., Zhang, H., Tagliasacchi, A., Liu, L., Li, G., Meng, M., Xiong, Y.: Partial intrinsic reflectional symmetry of 3D shapes. In: ACM Transactions on Graphics (TOG), vol. 28, p. 138. ACM (2009)

  5. Attene, M., Robbiano, F., Spagnuolo, M., Falcidieno, B.: Characterization of 3D shape parts for semantic annotation. Comput. Aided Des. 41(10), 756–763 (2009)

    Article  Google Scholar 

  6. Abacı, T., Vexo, F.: Bridging geometry and semantics for object manipulation and grasping. In: Proceedings of the 1st workshop towards Semantic Virtual Environments SVE05, pp. 110–119. ACM press (2005)

  7. Bar-Aviv, E., Rivlin, E.: Functional 3D object classification using simulation of embodied agent. In: BMVC, pp. 307–316 (2006)

  8. Grabner, H., Gall, J., Van Gool, L.: What makes a chair a chair? In: Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pp. 1529–1536 (2011)

  9. Attene, M., Biasotti, S., Mortara, M., Patanè, G., Spagnuolo, M., Falcidieno, B.: Computational methods for understanding 3D shapes. Comput. Graph. 30(3), 323–333 (2006)

    Article  Google Scholar 

  10. Biasotti, S., Falcidieno, B., Spagnuolo, M.: Extended reeb graphs for surface understanding and description. In: Borgefors, G., Nyström, I., Baja, G.S. (eds.) Discrete geometry for computer imagery. Lecture Notes in Computer Science, vol. 1953, pp. 185–197. Springer, Berlin (2000)

    Chapter  Google Scholar 

  11. Mitra, N., Wand, M., Richard Zhang, H., Cohen-Or, D., Kim, V., Huang, Q.-X.: Structure-aware shape processing. In: SIGGRAPH Asia 2013 Courses, p. 1. ACM (2013)

  12. Kim, V.G., Li, W., Mitra, N.J., Chaudhuri, S., DiVerdi, S., Funkhouser, T.: Learning part-based templates from large collections of 3D shapes. ACM Trans. Graph. 32(4), 70 (2013)

    Google Scholar 

  13. Kalogerakis, E., Hertzmann, A., Singh, K.: Learning 3D mesh segmentation and labeling. ACM Trans. Graph. 29(4), 102 (2010)

    Article  Google Scholar 

  14. Wang, Y. Xu, K., Li, J., Zhang, H., Shamir, A., Liu, L., Cheng, Z., Xiong, Y.: Symmetry hierarchy of man-made objects. In: Computer Graphics Forum, vol. 30, pp. 287–296. Wiley Online, Library (2011)

  15. Kai, X., Zhang, H., Cohen-Or, D., Chen, B.: Fit and diverse: set evolution for inspiring 3D shape galleries. ACM Trans. Graph. 31(4), 57 (2012)

    Google Scholar 

  16. Jiang, Y., Koppula, H., Saxena, A.: Hallucinated humans as the hidden context for labeling 3D scenes. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2993–3000 (2013)

  17. Gupta, A., Davis, L.S.: Objects in action: an approach for combining action understanding and object perception. In: IEEE Conference on Computer Vision and Pattern Recognition, 2007 (CVPR’07), pp. 1–8 (2007)

  18. Kai, X., Li, H., Zhang, H., Cohen-Or, D., Xiong, Y., Cheng, Z.-Q.: Style-content separation by anisotropic part scales. ACM Trans. Graph. 29(6), 184 (2010)

    Google Scholar 

  19. Hu, R., Fan, L., Liu, L.: Co-segmentation of 3D shapes via subspace clustering. In: Computer Graphics Forum, vol. 31, pp. 1703–1713. Wiley, New York (2012)

  20. Sidi, O., van Kaick, O., Kleiman, Y., Zhang, H., Cohen-Or, D.: Unsupervised co-segmentation of a set of shapes via descriptor-space spectral clustering. In: ACM Transactions on Graphics (TOG). ACM, vol. 30, p. 126 (2011)

  21. Reuter, M.: Hierarchical shape segmentation and registration via topological features of Laplace–Beltrami eigenfunctions. Int. J. Comput. Vis. 89(2–3), 287–308 (2010)

    Article  Google Scholar 

  22. Silberman, N., Fergus, R.: Indoor scene segmentation using a structured light sensor. In: 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp. 601–608 (2011)

  23. Koppula, H.S., Anand, A., Joachims, T., Saxena, A.: Semantic labeling of 3D point clouds for indoor scenes. In: Advances in Neural Information Processing Systems, pp. 244–252 (2011)

  24. Nan, L., Xie, K., Sharf, A.: A search-classify approach for cluttered indoor scene understanding. ACM Trans. Graph. 31(6), 137 (2012)

    Article  Google Scholar 

  25. Poser pro 2010. http://poser.smithmicro.com/poserpro.html (2010)

  26. Google 3D Warehouse. http://www.sketchup.google.com/3dwarehouse/ (2013)

  27. Jones, M.W., Baerentzen, J.A., Sramek, M.: 3D distance fields: a survey of techniques and applications. IEEE Trans. Vis. Comput. Graph. 12(4), 581–599 (2006)

    Article  Google Scholar 

  28. Gottschalk, S., Lin, M.C., Manocha, D.: Obbtree: a hierarchical structure for rapid interference detection. In: Proceedings of the 23rd annual conference on Computer graphics and interactive techniques. ACM, pp. 171–180 (1996)

  29. Fu, H., Cohen-Or, D., Dror, G., Sheffer, A.: Upright orientation of man-made objects. ACM Trans. Graph. 27, 42 (2008)

    Article  Google Scholar 

  30. Vladimir, V.: The nature of statistical learning theory. Springer, New York (2000)

    Google Scholar 

  31. Rifkin, R., Klautau, A.: In defense of one-vs-all classification. J. Mach. Learn. Res. 5, 101–141 (2004)

    MATH  MathSciNet  Google Scholar 

  32. Cignoni, P., Corsini, M., Ranzuglia, G.: Meshlab: an open-source 3D mesh processing system. Ercim News 73, 45–46 (2008)

    Google Scholar 

  33. Shilane, P., Min, P., Kazhdan, M., Funkhouser, T.: The Princeton shape benchmark. In: Proceedings of Shape Modeling Applications, 2004, pp. 167–178 (2004)

  34. Kazhdan, M., Funkhouser, T., Rusinkiewicz, S.: Rotation invariant spherical harmonic representation of 3D shape descriptors. In: Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing. Eurographics Association, pp. 156–164 (2003)

  35. Chen, D.Y., Tian, X.P., Shen, Y.T., Ouhyoung, M.: On visual similarity based 3D model retrieval. In: Computer graphics forum, vol. 22, pp. 223–232. Wiley, New York (2003)

  36. Veltkamp, R.C., Giezeman, G.J.: Shrec10 track: large scale retrieval. In: 3DOR, pp. 63–69. Wiley, New York (2010)

  37. Godil, A, Sun, X., Lian Z.: Visual similarity based 3D shape retrieval using bag-of-features. In: Shape Modeling International Conference (SMI), pp. 63–69 (2010)

  38. Fukunaga, K., Narendra, P.M.: A branch and bound algorithm for computing k-nearest neighbors. IEEE Trans. Comput. 100(7), 750–753 (1975)

    Article  MathSciNet  Google Scholar 

  39. Chang, C.C., Lin, C.J.: Libsvm: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2(3), 27 (2011)

    Article  Google Scholar 

  40. Zelnik-Manor, L., Perona, P.: Self-tuning spectral clustering. In: Advances in neural information processing systems, pp. 1601–1608 (2004)

Download references

Acknowledgments

The authors would like to thank the anonymous reviewers for their helpful comments. We also thank Yanzhen Wang for his comments for this work in the early stage, and Liangliang Nan for his source code of point cloud reconstruction.

Author information

Authors and Affiliations

  1. State Key Laboratory of High Performance Computing, School of Computer Science, National University of Defense Technology, Changsha, China

    Zhige Xie, Yueshan Xiong & Kai Xu

Authors
  1. Zhige Xie
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Yueshan Xiong
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Kai Xu
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding authors

Correspondence to Zhige Xie or Kai Xu.

Additional information

This work was partially supported by the Research Fund for the Doctoral Program of Higher Education of China (No. 20104307110003), The National Natural Science Foundation of China (No. 61379103, 61202333, 61303185) and China Postdoctoral Science Foundation (No. 2012M520392).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xie, Z., Xiong, Y. & Xu, K. AB3D: action-based 3D descriptor for shape analysis. Vis Comput 30, 591–601 (2014). https://doi.org/10.1007/s00371-014-0980-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-014-0980-z

Keywords