DOI QR코드

DOI QR Code

Retrieval of Non-rigid 3D Models Based on Approximated Topological Structure and Local Volume

  • Hong, Yiyu (Department of Copyright Protection, Sangmyung University) ;
  • Kim, Jongweon (Department of Electronics Engineering, Sangmyung University)
  • Received : 2017.01.22
  • Accepted : 2017.04.09
  • Published : 2017.08.31

Abstract

With the increasing popularity of 3D technology such as 3D printing, 3D modeling, etc., there is a growing need to search for similar models on the internet. Matching non-rigid shapes has become an active research field in computer graphics. In this paper, we present an efficient and effective non-rigid model retrieval method based on topological structure and local volume. The integral geodesic distances are first calculated for each vertex on a mesh to construct the topological structure. Next, each node on the topological structure is assigned a local volume that is calculated using the shape diameter function (SDF). Finally, we utilize the Hungarian algorithm to measure similarity between two non-rigid models. Experimental results on the latest benchmark (SHREC' 15 Non-rigid 3D Shape Retrieval) demonstrate that our method works well compared to the state-of-the-art.

Keywords

References

  1. A. Harris, "The Effects of In-home 3D Printing on Product Liability Law," Journal of Science Policy and Governance, vol. 6, issue. 1, February, 2015.
  2. D. Gupta, M. Tarlock, "3D Printing, Copyright Challenges, and the DMCA," New Matter, vol. 38, no. 3, 2013.
  3. L. Shapira, A. Shamir, and D. Cohen-Or, "Consistent mesh partitioning and skeletonisation using the shape diameter function," The Visual Computer, vol. 24, pp. 249-259, 2008. https://doi.org/10.1007/s00371-007-0197-5
  4. M. Hilaga, Y. Shinagawa, T. Kohmura, and T. Kunii, "Topology Matching for Fully Automatic Similarity Estimation of 3D Shapes," in Proc. of ACM SIGGRAPH '01, pp. 203-212, 2001.
  5. D. Chen, X. Tian, Y. Shen, M. Ouhyoung, "On visual similarity based 3D model retrieval," Eurographics, vol. 22, no. 3, pp. 223-232, 2003.
  6. G. Passalis, T. Theoharis, I. Kakadiaris, "PTK: A Novel Depth Buffer-Based Shape Descriptor for Three-Dimensional Object Retrieval," The Visual Computer, vol. 23, pp. 5-14, 2007.
  7. M. Kazhdan, T. Funkhouser, S. Rusinkiewicz, "Rotation invariant spherical harmonic representation of 3D shape descriptors," in Proc. of SGP '03: Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing, pp. 156-164. 2003.
  8. R. Osada, T. Funkhouser, B. Chazelle, D. Dobkin, "Shape distributions," ACM Transactions on Graphics, vol. 21, pp. 807-832, 2002. https://doi.org/10.1145/571647.571648
  9. Z. Lian, A. Godil, X. Sun, "Visual similarity based 3D shape retrieval using bag-of-features," in Proc. of SMI '10: Proceedings of the IEEE International Conference on Shape Modeling and Applications, pp. 25-36, 2010.
  10. Z. Lian, A. Godil, X. Sun, H. Zhang, "Non-rigid 3D shape retrieval using multidimensional scaling and bag-of-features," in Proc. of International Conference on Image Processing, pp. 3181-3184, 2010.
  11. K. Sfikas, T. Theoharis, I. Pratikakis, "Non-rigid 3D object retrieval using topological information guided by conformal factors," The visual Computer, vol. 28, pp. 943-955, 2012. https://doi.org/10.1007/s00371-012-0714-z
  12. M. Ben-Chen, C. Gotsman, "Characterizing shape using conformal factors," in Proc. of 3DOR '08: Proceedings of the 1st Eurographics conference on 3D Object Retrieval, pp. 1-8, 2008.
  13. M. Reuter, F. Wolter, N. Peinecke, "Laplace-Beltrami spectra as 'Shape-DNA' of surfaces and solids," Computer-Aided Design, vol. 38, pp. 342-366, 2006. https://doi.org/10.1016/j.cad.2005.10.011
  14. J. Sun, M. Ovsjanikov, L.J. Guibas, "A concise and provably informative multi-scale signature based on heat diffusion," Computer Graphics Forum, vol. 28, pp. 1383-1392, 2009.
  15. M. Aubry, U. Schlickewei, D. Cremers, "The wave kernel signature: a quantum mechanical approach to shape analysis," in Proc. of computational methods for the innovative design of electrical devices, pp. 1626-1633, 2011.
  16. C. Li, A. Ben Hamza, "Spatially aggregating spectral descriptors for nonrigid 3D shape retrieval: a comparative survey," Multimedia Systems, vol. 20, pp. 253-281, 2014. https://doi.org/10.1007/s00530-013-0318-0
  17. R. Gal, A. Shamir, D. Cohen-Or, "Pose-oblivious shape signature," IEEE Transactions on Visualization and Computer Graphics, vol. 13, pp. 261-271, 2007. https://doi.org/10.1109/TVCG.2007.45
  18. A. Agathos, I. Pratikakis, P. Papadakis, S.j. Perantonis, P.N. Azariadis, N.S. Sapidis, "3D articulated object retrieval using a graph-based representation," The Visual Computer, vol. 26, pp. 1301-1319, 2010. https://doi.org/10.1007/s00371-010-0523-1
  19. R. Kimmel, J.A. Sethian, "Computing geodesic paths on manifolds," in Proc. of the National Academy of Sciences of the United States of America, vol. 95, pp. 8431-8435, 1998.
  20. G. Peyr'e, L.D. Cohen, "Geodesic remeshing using front propagation," International Journal of Computer Vision, vol. 69, pp. 145-156, 2006. https://doi.org/10.1007/s11263-006-6859-3
  21. H.W. Kuhn, "The Hungarian method for the assignment problem," Naval Research Logistics, vol. 2, pp. 83-97, 1955. https://doi.org/10.1002/nav.3800020109
  22. P. Shilane, P. Min, M. Kazhdan, T. Funkhouser, "The Princeton Shape Benchmark," in Proc. of SMI '04: Proceedings of the Shape Modeling International 2004, pp. 167-178, 2004.
  23. J. Tangelder, R. Veltkamp, "A survey of content based 3D shape retrieval methods," Multimedia Tools and Applications, vol. 39, pp. 441-471, 2008. https://doi.org/10.1007/s11042-007-0181-0
  24. Z. Lian, A. Godil, B. Bustos, M. Daoudi, J. Hermans, S. Kawamura, Y. Kurita, G. Lavoue, H.V. Nguyen, R. Ohbuchi, Y. Ohkita, Y. Ohishi, F. Porikli, M. Reuter, I. Sipiran, D. Smeets, P. Suetens, H. Tabia, D. Vandermeulen, "A comparison of methods for non-rigid 3D shape retrieval," Pattern Recognition, vol. 46, pp. 449-461, 2013. https://doi.org/10.1016/j.patcog.2012.07.014
  25. Z. Lian, A. Godil, B. Bustos, M. Daoudi, J. Hermans, S. Kawamura, Y. Kurita, G. Lavoue, H. Nguyen, R. Ohbuchi, Y. Ohkita, Y. Ohishi, F. Porikli, M. Reuter, I. Sipiran, D. Smeets, P. Suetens, H. Tabia, D. Vandermeulen, "SHREC'11 track: shape retrieval on non-rigid 3D watertight meshes," in Proc. of 3DOR '11: Proceedings of the 4th Eurographics conference on 3D Object Retrieval, pp. 79-88. 2011.
  26. Z. Lian, J. Zhang, S. Choi, H. ElNaghy, J. El-Sana, T. Furuya, A. Giachetti, R.A. Guler, L. Lai, C. Li, H. Li, F.A. Limberger, R. Martin, R.U. Nakanishi, A.P. Neto, L.G. Nonato, R. Ohbuchi, K. Pevzner, D. Pickup, P. Rosin, A. Sharf, L. Sun, X. Sun, S. Tari, G. Unal, R.C. Wilson, " SHREC'15 Track: Non-rigid 3D Shape Retrieval," in Proc. of 3DOR Proceedings of the 2015 Eurographics Workshop on 3D Object Retrieval, pp. 107-120, 2015.
  27. M. Garland, Qslim Simplification Software, Available from: http://www.cs.cmu.edu/-/garland/quadrics/qslim.html [retrieved: July, 2016].
  28. M. Garland, P.S. Heckbert, "Surface simplification using quadric error metrics," in Proc. of SIGGRAPH 1997: Proceedings of the 24th annual conference on Computer graphics and interactive techniques, pp. 209-216, 1997.
  29. Conformal factor computation, Available from: http://en.pudn.com/downloads637/sourcecode/graph/detail2582972_en.html [retrieved: May, 2016]
  30. Y. Hong, J. Kim, "Non-Rigid 3D Model Retrieval Based on Topological Structure and Shape Diameter Function," in Proc. of ADVCOMP 2016: The Tenth International Conference on Advanced Engineering Computing and Application in Sciences, pp. 63-67, 2016.
  31. D. Smeets, T. Fabry, J. Hermans, D. Vandermeulen, P. Suetens, "Isometric Deformation Modelling for Object Recognition," in Proc. of The 13th International Conference on Computer Analysis of Images and Patterns (CAIP'09), pp. 757-765, 2009.

Cited by

  1. Improved Sliding Shapes for Instance Segmentation of Amodal 3D Object vol.12, pp.11, 2017, https://doi.org/10.3837/tiis.2018.11.021