“Geometric modeling in shape space” by Kilian, Mitra and Pottmann

  • ©Martin Kilian, Niloy J. Mitra, and Helmut Pottmann

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Title:

    Geometric modeling in shape space

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Abstract:


    We present a novel framework to treat shapes in the setting of Riemannian geometry. Shapes — triangular meshes or more generally straight line graphs in Euclidean space — are treated as points in a shape space. We introduce useful Riemannian metrics in this space to aid the user in design and modeling tasks, especially to explore the space of (approximately) isometric deformations of a given shape. Much of the work relies on an efficient algorithm to compute geodesics in shape spaces; to this end, we present a multi-resolution framework to solve the interpolation problem — which amounts to solving a boundary value problem — as well as the extrapolation problem — an initial value problem — in shape space. Based on these two operations, several classical concepts like parallel transport and the exponential map can be used in shape space to solve various geometric modeling and geometry processing tasks. Applications include shape morphing, shape deformation, deformation transfer, and intuitive shape exploration.

References:


    1. Alexa, M., Cohen-Or, D., and Levin, D. 2000. As-rigid-as-possible shape interpolation. In Proc. SIGGRAPH ’00, 157–164. Google ScholarDigital Library
    2. Allen, B., Curless, B., and Popović, Z. 2003. The space of human body shapes: reconstruction and parameterization from range scans. ACM Trans. Graphics 22, 3, 587–594. Google ScholarDigital Library
    3. Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., and Davis, J. 2005. SCAPE: shape completion and animation of people. ACM Trans. Graphics 24, 3, 408–416. Google ScholarDigital Library
    4. Berger, M. 1987. Geometry I, II. Springer.Google Scholar
    5. Botsch, M., Pauly, M., Gross, M., and Kobbelt, L. 2006. Primo: coupled prisms for intuitive surface modeling. In Symp. Geom. Processing, 11–20. Google ScholarDigital Library
    6. Bottema, O., and Roth, B. 1990. Theoretical kinematics. Dover Publ.Google Scholar
    7. Bronstein, A., Bronstein, M., and Kimmel, R. 2005. Isometric embedding of facial surfaces into S3. In Proc. of Scale-Space, 622–631. Google ScholarDigital Library
    8. Cecil, T. 1992. Lie Sphere Geometry. Springer.Google Scholar
    9. Charpiat, G., Faugeras, O., and Keriven, R. 2005. Approximations of shape metrics and application to shape warping and empirical statistics. Foundations of Comp. Math., 5, 1–58. Google ScholarDigital Library
    10. Charpiat, G., Keriven, R., Pons, J.-P., and Faugeras, O. 2005. Designing spatially coherent minimizing flows for variational problems based on active contours. In Proc. ICCV 2005, vol. 2, 1403–1408. Google ScholarDigital Library
    11. Cheng, H.-L., Edelsbrunner, H., and Fu, P. 1998. Shape space from deformation. In Proc. Pacific Graphics, 104–113. Google ScholarDigital Library
    12. Cox, T., and Cox, M. 2001. Multidimensional Scaling. CRC/Chapman and Hall.Google Scholar
    13. Do Carmo, M. P. 1992. Riemannian Geometry. Birkhäuser.Google Scholar
    14. Funck, W., Theisel, H., and Seidel, H. 2006. Vector field based shape deformations. ACM Trans. Graphics 25, 3, 1118–1125. Google ScholarDigital Library
    15. Garland, M., and Heckbert, P. 1997. Surface simplification using quadric error metrics. In ACM SIGGRAPH, 209–216. Google ScholarDigital Library
    16. Gelfand, I. M., and Fomin, S. V. 1963. Calculus of Variations. Prentice Hall.Google Scholar
    17. Hoppe, H. 1996. Progressive meshes. In ACM SIGGRAPH, 99–108. Google ScholarDigital Library
    18. Huang, J., Shi, X., Liu, X., Zhou, K., Wei, L., Teng, S., Bao, H., Guo, B., and Shum, H. 2006. Subspace gradient domain mesh deformation. ACM Trans. Graphics 25, 3, 1126–1134. Google ScholarDigital Library
    19. Igarashi, T., Moscovich, T., and Hughes, J. F. 2005. As-rigid-as-possible shape manipulation. ACM Trans. Graphics 24, 3, 1134–1141. Google ScholarDigital Library
    20. Ju, T., Schaefer, S., and Warren, J. 2005. Mean value coordinates for closed triangular meshes. ACM Trans. Graphics 24, 3, 561–566. Google ScholarDigital Library
    21. Kendall, D. G. 1984. Shape manifolds, procrustean metrics and complex projective spaces. Bull. London Math. Soc. 18, 81–121.Google ScholarCross Ref
    22. Kilian, M. 2007. Shapes, metrics, and their geodesics. Tech. Rep. 178, Vienna University of Technology.Google Scholar
    23. Kimmel, R., and Sethian, J. 1998. Computing geodesic paths on manifolds. Proc. Natl. Acad. Sci. 95, 8431–8435.Google ScholarCross Ref
    24. Klassen, E., Srivastava, A., Mio, W., and Joshi, S. H. 2004. Analysis of planar shapes using geodesic paths on shape spaces. IEEE PAMI 26, 3, 372–383. Google ScholarDigital Library
    25. Kraevoy, V., and Sheffer, A. 2004. Cross-parameterization and compatible remeshing of 3D models. ACM Trans. Graphics 23, 3, 861–869. Google ScholarDigital Library
    26. Kraevoy, V., and Sheffer, A. 2007. Mean-value geometry encoding. International Journal of Shape Modeling 12, 1.Google Scholar
    27. Lipman, Y., Sorkine, O., Levin, D., and Cohen-Or, D. 2005. Linear rotation-invariant coordinates for meshes. ACM Trans. Graphics 24, 3, 479–487. Google ScholarDigital Library
    28. Lipman, Y., Cohen-Or, D., Gal, R., and Levin, D. 2007. Volume and shape preservation vai moving frame manipulation. ACM Trans. Graphics 26, 1. Google ScholarDigital Library
    29. Liu, D. C., and Nocedal, J. 1989. On the limited memory BFGS method for large scale optimization. Math. Program. 45, 3, 503–528. Google ScholarDigital Library
    30. Memoli, F., and Sapiro, G. 2001. Fast computation of weighted distance functions and geodesics on implicit hyper-surfaces. J. Comput. Phys. 173, 730–764. Google ScholarDigital Library
    31. Mémoli, F., and Sapiro, G. 2004. Comparing point clouds. In Symp. Geometry Processing, 32–40. Google ScholarDigital Library
    32. Michor, P. W., and Mumford, D. 2006. Riemannian geometries on spaces of plane curves. J. Eur. Math. Soc. 8, 1–48.Google ScholarCross Ref
    33. Pottmann, H., and Wallner, J. 2001. Computational Line Geometry. Springer. Google ScholarDigital Library
    34. Schreiner, J., Asirvatham, A., Praun, E., and Hoppe, H. 2004. Inter-surface mapping. ACM Trans. Graphics 23, 3, 870–877. Google ScholarDigital Library
    35. Sloan, P.-P. J., Rose, C. F., and Cohen, M. F. 2001. Shape by example. In Proc. of the 2001 symposium on interactive 3D graphics, 135–143. Google ScholarDigital Library
    36. Sorkine, O., Lipman, Y., Cohen-Or, D., Alexa, M., Rössl, C., and Seidel, H.-P. 2004. Laplacian surface editing. In Symp. Geom. Processing, 179–188. Google ScholarDigital Library
    37. Sumner, R. W., and Popovič, J. 2004. Deformation transfer for triangle meshes. ACM Trans. Graphics 23, 3, 399–405. Google ScholarDigital Library
    38. Xu, D., Zhang, H., Wang, Q., and Bao, H. 2005. Poisson shape interpolation. In SPM ’05: Proc. ACM Symp. on Solid and Physical Modeling, 267–274. Google ScholarDigital Library
    39. Yezzi, A., and Mennucci, A. 2005. Conformal metrics and true “gradient flows” for curves. In Proc. ICCV ’05, 913–919. Google ScholarDigital Library


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