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On length measures of planar closed curves and the comparison of convex shapes

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Abstract

In this paper, we revisit the notion of length measures associated to planar closed curves. These are a special case of area measures of hypersurfaces which were introduced early on in the field of convex geometry. The length measure of a curve is a measure on the circle \(\mathbb {S}^1\) that intuitively represents the length of the portion of curve which tangent vector points in a certain direction. While a planar closed curve is not characterized by its length measure, the fundamental Minkowski–Fenchel–Jessen theorem states that length measures fully characterize convex curves modulo translations, making it a particularly useful tool in the study of geometric properties of convex objects. The present work, that was initially motivated by problems in shape analysis, introduces length measures for the general class of Lipschitz immersed and oriented planar closed curves, and derives some of the basic properties of the length measure map on this class of curves. We then focus specifically on the case of convex shapes and present several new results. First, we prove an isoperimetric characterization of the unique convex curve associated to some length measure given by the Minkowski–Fenchel–Jessen theorem, namely that it maximizes the signed area among all the curves sharing the same length measure. Second, we address the problem of constructing a distance with associated geodesic paths between convex planar curves. For that purpose, we introduce and study a new distance on the space of length measures that corresponds to a constrained variant of the Wasserstein metric of optimal transport, from which we can induce a distance between convex curves. We also propose a primal-dual algorithm to numerically compute those distances and geodesics, and show a few simple simulations to illustrate the approach.

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References

  1. Abdallah, H., Mérigot, Q.: On the reconstruction of convex sets from random normal measurements. In: Proceedings of the Thirtieth Annual Symposium on Computational Geometry, pp. 300–307(2014)

  2. Alexandrov, A..: Zur theorie der gemischten volumina von konvexen koörpern. i. verallgemeinerung einiger begriffe der theorie von konvexen körpern (1937)

  3. Allard, W.K.: On the first variation of a varifold. Ann. Math. 95, 417–491 (1972)

    Article  MathSciNet  Google Scholar 

  4. Ambrosio, L., Fusco, N., Pallara, D.: Functions of Bounded Variation and Free Discontinuity Problems. Clarendon Press, Oxford (2000)

    MATH  Google Scholar 

  5. Aronszajn, N.: Theory of reproducing kernels. Trans. Am. Math. Soc. 68, 337–404 (1950)

    Article  MathSciNet  Google Scholar 

  6. Benamou, J.-D., Brenier, Y.: A computational fluid mechanics solution to the Monge–Kantorovich mass transfer problem. Numer. Math. 84(3), 375–393 (2000)

    Article  MathSciNet  Google Scholar 

  7. Blaschke, W.: Kreis und Kugel. Verlag von Veit Comp, Leipzig (1916)

    Book  Google Scholar 

  8. Böröczky, K., Bárány, I., Makai, E., Pach, J.: Maximal volume enclosed by plates and proof of the chessboard conjecture. Discrete Math. 60, 101–120 (1986)

    Article  MathSciNet  Google Scholar 

  9. Brezis, H.: Functional Analysis, Sobolev Spaces and Partial Differential Equations. Universitext. Springer, New York (2010)

    Google Scholar 

  10. Buet, B., Leonardi, G.P., Masnou, S.: Discretization and approximation of surfaces using varifolds. Geom. Flows 3(1), 28–56 (2018)

    Article  MathSciNet  Google Scholar 

  11. Cardaliaguet, P., Carlier, G., Nazaret, B.: Geodesics for a class of distances in the space of probability measures. Calc. Var. Partial. Differ. Equ. 48(3–4), 395–420 (2013)

    Article  MathSciNet  Google Scholar 

  12. Carlier, G.: On a theorem of Alexandrov. J. Nonlinear Convex Anal. 5(1), 49–58 (2004)

    MathSciNet  MATH  Google Scholar 

  13. Chambolle, A., Pock, T.: A first-order primal-dual algorithm for convex problems with applications to imaging. J. Math. Imaging Vis. 40(1), 120–145 (2011)

    Article  MathSciNet  Google Scholar 

  14. Charon, N., Trouvé, A.: The varifold representation of nonoriented shapes for diffeomorphic registration. SIAM J. Imaging Sci. 6(4), 2547–2580 (2013)

    Article  MathSciNet  Google Scholar 

  15. Chizat, L., Peyré, G., Schmitzer, B., Vialard, F.-X.: An interpolating distance between optimal transport and Fisher–Rao metrics. Found. Comput. Math. 18(1), 1–44 (2018)

    Article  MathSciNet  Google Scholar 

  16. Cohen-Steiner, D., Morvan, J.M.: Restricted delaunay triangulation and normal cycle. In: Proceedings of the nineteenth annual symposium on Computational geometry pp 312–321 (2003)

  17. Cuturi, M.: Sinkhorn distances: lightspeed computation of optimal transportation distances. Adv. Neural Inf. Process. Syst. 26, 2292–2300 (2013)

  18. Delon, J., Salomon, J., Sobolevski, A.: Fast transport optimization for Monge costs on the circle. SIAM J. Appl. Math. 70(7), 2239–2258 (2010)

    Article  MathSciNet  Google Scholar 

  19. Durrleman, S., Pennec, X., Trouvé, A., Ayache, N.: Statistical models of sets of curves and surfaces based on currents. Med. Image Anal. 13(5), 793–808 (2009)

    Article  Google Scholar 

  20. Evans, L., Gariepy, R.: Measure Theory and Fine Properties of Functions. CRC Press, Boca Raton (2015)

    Book  Google Scholar 

  21. Fáry, I., Makai, E.: Isoperimetry in variable metric. Stud. Sci. Math. Hung. 17, 143–158 (1982)

    MathSciNet  MATH  Google Scholar 

  22. Federer, H.: Geometric Measure Theory. Springer, Berlin (1969)

    MATH  Google Scholar 

  23. Fenchel, W., Jessen, B.: Mengenfunktionen und konvexe körper. Levin & Munksgaard, Matematisk-fysiske meddelelser (1938)

  24. Gardner, R.: The Brunn–Minkowski inequality. Bull. Am. Math. Soc. 39(3), 355–405 (2002)

    Article  MathSciNet  Google Scholar 

  25. Gardner, R., Kiderlen, M., Milanfar, P.: Convergence of algorithms for reconstructing convex bodies and directional measures. Ann. Stat. 34(3), 1331–1374 (2006)

    Article  MathSciNet  Google Scholar 

  26. Glaunès, J., Trouvé, A., Younes, L.: Diffeomorphic matching of distributions: a new approach for unlabelled point-sets and sub-manifolds matching. Comput. Vis. Pattern Recognit. 2, 712–718 (2004)

    Google Scholar 

  27. Glaunès, J., Vaillant, M.: Surface matching via currents. In: Proceedings of Information Processing in Medical Imaging (IPMI). Lecture Notes in Computer Science, vol. 3565, pp. 381–392 (2006)

  28. Gretton, A., Borgwardt, K., Rasch, M., Schölkopf, B., Smola, A.J.: A kernel method for the two-sample-problem. Adv. Neural Inf. Process. Syst. 19, 513–520 (2007)

  29. Gu, X., Luo, F., Sun, J., Yau, S.-T.: Variational principles for Minkowski type problems, discrete optimal transport, and discrete Monge–Ampère equations. Asian J. Math. 20(2), 383–398 (2016)

    Article  MathSciNet  Google Scholar 

  30. Hebert, M., Ikeuchi, K., Delingette, H.: A spherical representation for recognition of free-form surfaces. IEEE Trans. Pattern Anal. Mach. Intell. 17(7), 681–690 (1995)

    Article  Google Scholar 

  31. Heijmans, H., Tuzikov, A.: Similarity and symmetry measures for convex shapes using Minkowski addition. IEEE Trans. Pattern Anal. Mach. Intell. 20(9), 980–993 (1998)

    Article  Google Scholar 

  32. Hu, Y., Hudelson, M., Krishnamoorthy, B., Tumurbaatar, A., Vixie, K.R.: Median shapes. J. Comput. Geom. 10, 322–388 (2019)

    MathSciNet  MATH  Google Scholar 

  33. Kaltenmark, I., Charlier, B., Charon, N.: A general framework for curve and surface comparison and registration with oriented varifolds. In: Computer Vision and Pattern Recognition (CVPR) (2017)

  34. Lachand-Robert, T., Oudet, E.: Minimizing within convex bodies using a convex hull method. SIAM J. Optim. 16(2), 368–379 (2005)

    Article  MathSciNet  Google Scholar 

  35. Letac, G.: Mesures sur le cercle et convexes du plan. Annales scientifiques de l’Université de Clermont-Ferrand 2. Série Probabilités et applications 76(1), 35–65 (1983)

    MathSciNet  MATH  Google Scholar 

  36. Li, Y., Swersky, K., Zemel, R.: Generative moment matching networks. In: International Conference on Machine Learning, pp. 1718–1727 (2015)

  37. Liero, M., Mielke, A., Savaré, G.: Optimal transport in competition with reaction: the Hellinger–Kantorovich distance and geodesic curves. SIAM J. Math. Anal. 48(4), 2869–2911 (2016)

    Article  MathSciNet  Google Scholar 

  38. Michor, P.W., Mumford, D.: Riemannian geometries on spaces of plane curves. J. Eur. Math. Soc. 8, 1–48 (2006)

    Article  MathSciNet  Google Scholar 

  39. Papadakis, N., Peyré, G., Oudet, E.: Optimal transport with proximal splitting. SIAM J. Imaging Sci. 7(1), 212–238 (2014)

    Article  MathSciNet  Google Scholar 

  40. Piccoli, B., Rossi, F.: Generalized Wasserstein distance and its application to transport equations with source. Arch. Ration. Mech. Anal. 211(1), 335–358 (2014)

    Article  MathSciNet  Google Scholar 

  41. Prince, J.L., Willsky, A.S.: Reconstructing convex sets from support line measurements. IEEE Trans. Pattern Anal. Mach. Intell. 12(4), 377–389 (1990)

    Article  Google Scholar 

  42. Rockafellar, R.: Integrals which are convex functionals. II. Pac. J. Math. 39(2), 439–469 (1971)

    Article  MathSciNet  Google Scholar 

  43. Roussillon, P., Glaunès, J.: Kernel metrics on normal cycles and application to curve matching. SIAM J. Imaging Sci. 9(4), 1991–2038 (2016)

    Article  MathSciNet  Google Scholar 

  44. Schneider, R.: Convex Bodies: The Brunn–Minkowski Theory. Encyclopedia of Mathematics and Its Applications, 2nd edn. Cambridge University Press, Cambridge (2013)

    Google Scholar 

  45. Sriperumbudur, B., Fukumizu, K., Lanckriet, G.: Universality, characteristic kernels and RKHS embedding of measures. J. Mach. Learn. Res. 12, 2389–2410 (2011)

    MathSciNet  MATH  Google Scholar 

  46. Van Kreveld, M., Schwarzkopf, O., de Berg, M., Overmars, M.: Computational Geometry Algorithms and Applications. Springer, Berlin (2000)

    MATH  Google Scholar 

  47. Villani, C.: Optimal Transport: Old and New, vol. 338. Springer, Berlin (2008)

    MATH  Google Scholar 

  48. Younes, L.: Shapes and Diffeomorphisms. Springer, Berlin (2019)

    Book  Google Scholar 

  49. Zouaki, H.: Representation and geometric computation using the extended Gaussian image. Pattern Recogn. Lett. 24(9–10), 1489–1501 (2003)

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank F-X Vialard for some useful insights in relation to the optimal transport model presented in this paper. This work was supported by the National Science Foundation (NSF) under the Grant 1945224.

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This work was in part supported by the National Science Foundation (NSF) under the Grant 1945224.

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Correspondence to Nicolas Charon.

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Charon, N., Pierron, T. On length measures of planar closed curves and the comparison of convex shapes. Ann Glob Anal Geom 60, 863–901 (2021). https://doi.org/10.1007/s10455-021-09795-0

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