3D Human Shapes Correspondence using the Principal Curvature Fields on a Local Surface Parametrization

In this paper, we address the problem of the correspondence b etween 3D non-rigid human shapes. We propose a local surface description around the 3D human body extremi i s. It is based on the mean of principal curvature fields values on the intrinsic Darcyan parametriz ation constructed around these points. The similarity between the resulting descriptors is, then, measured in the sense of theL2 distance. Experiments on a several human objects from the TOSCA dataset confirm the accuracy of t he proposed approach.

[1]  Thomas A. Funkhouser,et al.  Fuzzy Geodesics and Consistent Sparse Correspondences For: eformable Shapes , 2010 .

[2]  Vladimir G. Kim,et al.  Blended intrinsic maps , 2011, SIGGRAPH 2011.

[3]  Andrew W. Fitzgibbon,et al.  The Vitruvian manifold: Inferring dense correspondences for one-shot human pose estimation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[4]  J. Keyser,et al.  Multiple Shape Correspondence by Dynamic Programming , 2014 .

[5]  Mark Meyer,et al.  Discrete Differential-Geometry Operators for Triangulated 2-Manifolds , 2002, VisMath.

[6]  Lijun Jiang,et al.  Partial Shape Matching of 3D Models Based on the Laplace-Beltrami Operator Eigenfunction , 2013, J. Multim..

[7]  Faouzi Ghorbel,et al.  A stable and accurate multi-reference representation for surfaces of R3: Application to 3D faces description , 2013, 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).

[8]  Ron Kimmel,et al.  Spectral Generalized Multi-dimensional Scaling , 2013, International Journal of Computer Vision.

[9]  Qi-Xing Huang,et al.  Dense Human Body Correspondences Using Convolutional Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[10]  Ron Kimmel,et al.  Generalized multidimensional scaling: A framework for isometry-invariant partial surface matching , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Eugene Zhang,et al.  Pairwise Harmonics for Shape Analysis , 2013, IEEE Transactions on Visualization and Computer Graphics.

[12]  Leonidas J. Guibas,et al.  One Point Isometric Matching with the Heat Kernel , 2010, Comput. Graph. Forum.

[13]  Alexander M. Bronstein,et al.  Regularized Partial Matching of Rigid Shapes , 2008, ECCV.

[14]  Laurent D. Cohen,et al.  Global Minimum for Active Contour Models: A Minimal Path Approach , 1997, International Journal of Computer Vision.

[15]  D'arcy W. Thompson On growth and form i , 1943 .

[16]  Guillermo Sapiro,et al.  A Gromov-Hausdorff Framework with Diffusion Geometry for Topologically-Robust Non-rigid Shape Matching , 2010, International Journal of Computer Vision.

[17]  Daniel Cohen-Or,et al.  Deformation‐Driven Shape Correspondence , 2008, Comput. Graph. Forum.

[18]  J A Sethian,et al.  Computing geodesic paths on manifolds. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[19]  T. Funkhouser,et al.  Möbius voting for surface correspondence , 2009, SIGGRAPH 2009.

[20]  Ghassan Hamarneh,et al.  A Survey on Shape Correspondence , 2011, Comput. Graph. Forum.

[21]  Thomas A. Funkhouser,et al.  Möbius voting for surface correspondence , 2009, ACM Trans. Graph..