Laser & Optoelectronics Progress, Volume. 57, Issue 18, 181507(2020)

Calculation of Three-Dimensional shape Correspondence Based on Data-Driven Functional Map

Yang Jun* and Zhao Jinlong
Author Affiliations
  • School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou Gansu 730070, China
  • show less
    References(22)

    [1] Yang J, Li L J, Tian Z H et al. Research on shape correspondence of 3D isometric models differing by non-rigid deformations[J]. Journal of Frontiers of Computer Science & Technology, 8, 1009-1016(2014).

    [3] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 770-778(2016).

    [4] Charles R Q, Su H, Mo K C et al[2019-12-18]. PointNet: deep learning on point sets for 3D classification and segmentation [2019-12-18].https: ∥arxiv., org/abs/1612, 00593.

    [5] Qi C R, Yi L, Su H et al[2019-12-15]. PointNet++: deep hierarchical feature learning on point sets in a metric space [2019-12-15].https:∥arxiv., org/abs/1706, 02413.

    [6] Corman É, Ovsjanikov M, Chambolle A. Supervised descriptor learning for non-rigid shape matching[M]. ∥Agapito L, Bronstein M, Rother C, et al. Computer Vision-ECCV 2014. Lecture Notes in Computer Science. Cham: Springer, 8928, 283-298(2014).

    [7] Salti S. Tombari F, di Stefano L. SHOT: unique signatures of histograms for surface and texture description[J]. Computer Vision and Image Understanding, 125, 251-264(2014).

    [8] Sun J, Ovsjanikov M, Guibas L. A concise and provably informative multi-scale signature based on heat diffusion[J]. Computer Graphics Forum, 28, 1383-1392(2009).

    [9] Aubry M, Schlickewei U, Cremers D. The wave kernel signature: a quantum mechanical approach to shape analysis. [C]∥2011 IEEE International Conference on Computer Vision Workshops, November 6-13, 2011, Barcelona, Spain. New York: IEEE, 1626-1633(2011).

    [10] Yang J, Yan H, Wang M Z. Calculation of correspondences between three-dimensional isometric shapes with the use of a fused feature descriptor[J]. Journal of Image and Graphics, 21, 628-635(2016).

    [11] Ovsjanikov M, Ben-Chen M, Solomon J et al. Functional maps: a flexible representation of maps between shapes[J]. ACM Transactions on Graphics, 31, 30(2012).

    [12] Yang J, Yan H. An algorithm for calculating shape correspondences using functional maps by calibrating base matrix of 3D shapes[J]. Geomatics and Information Science of Wuhan University, 43, 1518-1525(2018).

    [13] Ren J, Poulenard A, Wonka P et al. Continuous and orientation-preserving correspondences via functional maps[J]. ACM Transactions on Graphics, 37, 248-263(2019).

    [14] Huang H B, Kalogerakis E, Chaudhuri S et al. Learning local shape descriptors from part correspondences with multiview convolutional networks[J]. ACM Transactions on Graphics, 37, 1-14(2018).

    [15] Masci J, Boscaini D, Bronstein M M et al. Geodesic convolutional neural networks on Riemannian manifolds. [C]∥2015 IEEE International Conference on Computer Vision Workshop (ICCVW), December 7-13, 2015, Santiago, Chile. New York: IEEE, 832-840(2015).

    [16] Litany O, Remez T, Rodolà E et al. Deep functional maps: structured prediction for dense shape correspondence. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 5660-5668(2017).

    [17] Aflalo Y, Brezis H, Kimmel R. On the optimality of shape and data representation in the spectral domain[J]. Siam Journal on Imaging Sciences, 8, 1141-1160(2015).

    [18] Eynard D, Rodolà E, Glashoff K et al. Coupled functional maps. [C]∥2016 Fourth International Conference on 3D Vision (3DV), October 25-28, 2016, Stanford, CA, USA. New York: IEEE, 399-407(2016).

    [19] Rustamov R M, Ovsjanikov M, Azencot O et al. Map-based exploration of intrinsic shape differences and variability[J]. ACM Transactions on Graphics, 32, 72-83(2013).

    [20] Ren J, Panine M, Wonka P et al. Structured regularization of functional map computations[J]. Computer Graphics Forum, 38, 39-53(2019).

    [21] Nogneng D, Ovsjanikov M. Informative descriptor preservation via commutativity for shape matching[J]. Computer Graphics Forum, 36, 259-267(2017).

    [22] Bogo F, Romero J, Loper M et al. FAUST: dataset and evaluation for 3D mesh registration. [C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 3794-3801(2014).

    Tools

    Get Citation

    Copy Citation Text

    Yang Jun, Zhao Jinlong. Calculation of Three-Dimensional shape Correspondence Based on Data-Driven Functional Map[J]. Laser & Optoelectronics Progress, 2020, 57(18): 181507

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Machine Vision

    Received: Dec. 26, 2019

    Accepted: --

    Published Online: Sep. 2, 2020

    The Author Email:

    DOI:10.3788/LOP57.181507

    Topics