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Research Article | Open Access

Skeleton-based canonical forms for non-rigid 3D shape retrieval

School of Computer Science and Informatics, Cardiff University, Cardiff, CF24 3AA, UK.
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Abstract

The retrieval of non-rigid 3D shapes is an important task. A common technique is to simplify this problem to a rigid shape retrieval task by producing a bending-invariant canonical form for each shape in the dataset to be searched. It is common for these techniques to attempt to “unbend” a shape by applying multidimensional scaling (MDS) to the distances between points on the mesh, but this leads to unwanted local shape distortions. We instead perform the unbending on the skeleton of the mesh, and use this to drive the deformation of the mesh itself. This leads to computational speed-up, and reduced distortion of local shape detail. We compare our method against other canonical forms: our experiments show that our method achieves state-of-the-art retrieval accuracy in a recent canonical forms benchmark, and only a small drop in retrieval accuracy over the state-of-the-art in a second recent benchmark, while being significantly faster.

Keywords

canonical formsshape retrievalskeletonspose invariance

References

[1]
Li, B.; Godil, A.; Aono, M.; Bai, X.; Furuya, T.; Li, L.; López-Sastre, R.; Johan, H.; Ohbuchi, R.; Redondo-Cabrera, C.; Tatsuma, A.; Yanagimachi, T.; Zhang, S. SHREC ’12 track: Generic 3D shape retrieval. In: Proceedings of the 5th Eurographics Conference on 3D Object Retrieval, 119-126, 2012.
[2]
Elad, A.; Kimmel, R. On bending invariant signatures for surfaces. IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 25, No. 10, 1285-1295, 2003.
Crossref Google Scholar
[3]
Pickup, D.; Sun, X.; Rosin, P. L.; Martin, R. R.; Cheng, Z.; Nie, S.; Jin, L. Canonical forms for non-rigid 3D shape retrieval. In: Proceedings of the 2015 Eurographics Workshop on 3D Object Retrieval, 99-106, 2015.
Crossref
[4]
Chen, D.-Y.; Tian, X.-P.; Shen, Y.-T.; Ouhyoung, M. On visual similarity based 3D model retrieval. Computer Graphics Forum Vol. 22, No. 3, 223-232, 2003.
Crossref Google Scholar
[5]
Johnson, A. E.; Hebert, M. Using spin images for efficient object recognition in cluttered 3D scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 21, No. 5, 433-449, 1999.
Crossref Google Scholar
[6]
Tangelder, J. W. H.; Veltkamp, R. C. A survey of content based 3D shape retrieval methods. Multimedia Tools and Applications Vol. 39, No. 3, 441-471, 2008.
Crossref Google Scholar
[7]
Boyer, E.; Bronstein, A. M.; Bronstein, M. M.; Bustos, B.; Darom, T.; Horaud, R.; Hotz, I.; Keller, Y.; Keustermans, J.; Kovnatsky, A.; Litmany, R.; Reininghaus, J.; Sipiran, I.; Smeets, D.; Suetens, P.; Vandermeulen, D.; Zaharescu, A.; Zobel, V. SHREC 2011: Robust feature detection and description benchmark. In: Proceedings of the 4th Eurographics Conference on 3D Object Retrieval, 71-78, 2011.
[8]
Smeets, D.; Keustermans, J.; Vandermeulen, D.; Suetens, P. meshSIFT: Local surface features for 3D face recognition under expression variations and partial data. Computer Vision and Image Understanding Vol. 117, No. 2, 158-169, 2013.
Crossref Google Scholar
[9]
Ben-Chen, M.; Gotsman, C. Characterizing shape using conformal factors. In: Proceedings of the 1st Eurographics Conference on 3D Object Retrieval, 1-8, 2008.
[10]
Giachetti, A.; Lovato, C. Radial symmetry detection and shape characterization with the multiscale area projection transform. Computer Graphics Forum Vol. 31, No. 5, 1669-1678, 2012.
Crossref Google Scholar
[11]
Sun, J.; Ovsjanikov, M.; Guibas, L. A concise and provably informative multi-scale signature based on heat diffusion. Computer Graphics Forum Vol. 28, No. 5, 1383-1392, 2009.
Crossref Google Scholar
[12]
Lian, Z.; Zhang, J.; Choi, S.; ElNaghy, H.; El-Sana, J.; Furuya, T.; Giachetti, A.; Guler, R. A.; Lai, L.; Li, C.; Li, H.; Limberger, F. A.; Martin, R.; Nakanishi, R. U.; Neto, A. P.; Nonato, L. G.; Ohbuchi, R.; Pevzner, K.; Pickup, D.; Rosin, P.; Sharf, A.; Sun, L.; Sun, X.; Tari, S.; Unal, G.; Wilson, R. C. Non-rigid 3D shape retrieval. In: Proceedings of the 2015 Eurographics Workshop on 3D Object Retrieval, 107-120, 2015.
[13]
Pickup, D.; Sun, X.; Rosin, P. L.; Martin, R. R.; Cheng, Z.; Lian, Z.; Aono, M.; Hamza, A. B.; Bronstein, A.; Bronstein, M.; Bu, S.; Castellani, U.; Cheng, S.; Garro, V.; Giachetti, A.; Godil, A.; Han, J.; Johan, H.; Lai, L.; Li, B.; Li, C.; Li, H.; Litman, R.; Liu, X.; Liu, Z.; Lu, Y.; Tatsuma, A.; Ye, J. Shape retrieval of non-rigid 3D human models. In: Proceedings of the 7th Eurographics Workshop on 3D Object Retrieval, 101-110, 2014.
[14]
Hilaga, M.; Shinagawa, Y.; Kohmura, T.; Kunii, T. L. Topology matching for fully automatic similarity estimation of 3D shapes. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, 203-212, 2001.
Crossref
[15]
Sfikas, K.; Theoharis, T.; Pratikakis, I. Non-rigid 3D object retrieval using topological information guided by conformal factors. The Visual Computer Vol. 28, No. 9, 943-955, 2012.
Crossref Google Scholar
[16]
Reuter, M.; Wolter, F.-E.; Peinecke, N. Laplace–Beltrami spectra as ‘Shape-DNA’ of surfaces and solids. Computer-Aided Design Vol. 38, No. 4, 342-366, 2006.
Crossref Google Scholar
[17]
Smeets, D.; Hermans, J.; Vandermeulen, D.; Suetens, P. Isometric deformation invariant 3D shape recognition. Pattern Recognition Vol. 45, No. 7, 2817-2831, 2012.
Crossref Google Scholar
[18]
Shamai, G.; Zibulevsky, M.; Kimmel, R. Accelerating the computation of canonical forms for 3D nonrigid objects using multidimensional scaling. In: Proceedings of the 2015 Eurographics Workshop on 3D Object Retrieval, 71-78, 2015.
[19]
Lian, Z.; Godil, A.; Xiao, J. Feature-preserved 3D canonical form. International Journal of Computer Vision Vol. 102, No. 1, 221-238, 2013.
Crossref Google Scholar
[20]
Wang, X.-L.; Zha, H. Contour canonical form: An efficient intrinsic embedding approach to matching non-rigid 3D objects. In: Proceedings of the 2nd ACM International Conference on Multimedia Retrieval, Article No. 31, 2012.
Crossref
[21]
Pickup, D.; Sun, X.; Rosin, P. L.; Martin, R. R. Euclidean-distance-based canonical forms for non-rigid 3D shape retrieval. Pattern Recognition Vol. 48, No. 8, 2500-2512, 2015.
Crossref Google Scholar
[22]
Boscaini, D.; Girdziušas, R.; Bronstein, M. M. Coulomb shapes: Using electrostatic forces for deformation-invariant shape representation. In: Proceedings of the 7th Eurographics Workshop on 3D Object Retrieval, 9-15, 2014.
[23]
Crane, K.; Weischedel, C.; Wardetzky, M. Geodesics in heat: A new approach to computing distance based on heat flow. ACM Transactions on Graphics Vol. 32, No. 5, Article No. 152, 2013.
Crossref Google Scholar
[24]
Ying, X.; Xin, S.-Q.; He, Y. Parallel chen-han (PCH) algorithm for discrete geodesics. ACM Transactions on Graphics Vol. 33, No. 1, Article No. 9, 2014.
Crossref Google Scholar
[25]
Lian, Z.; Godil, A.; Bustos, B.; Daoudi, M.; Hermans, J.; Kawamura, S.; Kurita, Y.; Lavoué, G.; Nguyen, H. V.; Ohbuchi, R.; Ohkita, Y.; Ohishi, Y.; Porikli, F.; Reuter, M.; Sipiran, I.; Smeets, D.; Suetens, P.; Tabia, H.; Vandermeulen, D. SHREC ’11 track: Shape retrieval on non-rigid 3D watertight meshes. In: Proceedings of the 4th Eurographics Conference on 3D Object Retrieval, 79-88, 2011.
[26]
Lian, Z.; Godil, A.; Sun, X.; Xiao, J. CM-BOF: Visual similarity-based 3D shape retrieval using clock matching and bag-of-features. Machine Vision and Applications Vol. 24, No. 8, 1685-1704, 2013.
Crossref Google Scholar
[27]
Kimmel, R.; Sethian, J. A. Computing geodesic paths on manifolds. Proceedings of the National Academy of Sciences of the United States of the America Vol. 95, No. 15, 8431-8435, 1998.
Crossref Google Scholar
[28]
Borg, I.; Groenen, P. J. F. Modern Multidimensional Scaling: Theory and Applications. Springer-Verlag New York, 2005.
[29]
Au, O. K.-C.; Tai, C.-L.; Chu, H.-K.; Cohen-Or, D.; Lee, T.-Y. Skeleton extraction by mesh contraction. In: Proceedings of ACM SIGGRAPH 2008 Papers, Article No. 44, 2008.
[30]
Yan, H.-B.; Hu, S.-M.; Martin, R.; Yang, Y.-L. Shape deformation using a skeleton to drive simplex transformations. IEEE Transactions on Visualization and Computer Graphics Vol. 14, No. 3, 693-706, 2008.
Crossref Google Scholar
[31]
Baeza-Yates, R. A.; Ribeiro-Neto, B. A. Modern Information Retrieval: The Concepts and Technology behind Search, 2nd edn. Harlow, England: Pearson Education Ltd., 2011.
Computational Visual Media
Volume 2 Issue 3,
September 2016
Pages 231-243
DOI: 10.1007/s41095-016-0045-5
Cite this article:
Pickup D, Sun X, Rosin PL, et al. Skeleton-based canonical forms for non-rigid 3D shape retrieval. Computational Visual Media, 2016, 2(3): 231-243. https://doi.org/10.1007/s41095-016-0045-5

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Revised: 26 January 2016
Accepted: 20 February 2016
Published: 14 April 2016
© The Author(s) 2016

This article is published with open access at Springerlink.com

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