“Motion graphs for unstructured textured meshes” by Prada, Kazhdan and Chuang

  • ©Fabian Prada, Michael Kazhdan, Ming Chuang, Alvaro Collet, and Hugues Hoppe




    Motion graphs for unstructured textured meshes

Session/Category Title:   MAPPINGS




    Scanned performances are commonly represented in virtual environments as sequences of textured triangle meshes. Detailed shapes deforming over time benefit from meshes with dynamically evolving connectivity. We analyze these unstructured mesh sequences to automatically synthesize motion graphs with new smooth transitions between compatible poses and actions. Such motion graphs enable natural periodic motions, stochastic playback, and user-directed animations. The main challenge of unstructured sequences is that the meshes differ not only in connectivity but also in alignment, shape, and texture. We introduce new geometry processing techniques to address these problems and demonstrate visually seamless transitions on high-quality captures.


    1. Aksoylu, B., Khodakovsky, A., and Schröder, P. 2005. Multilevel solvers for unstructured surface meshes. SIAM Journal of Scientific Computing, 26:1146–1165. Google ScholarDigital Library
    2. Alvarez, L., Esclarín, J., Lefébure, M., and Sánchez, J. 1999. A PDE model for computing the optical flow. In XVI Congreso de Ecuaciones Diferenciales y Aplicaciones.Google Scholar
    3. Arikan, O. and Forsyth, D. A. 2002. Interactive motion generation from examples. ACM Trans. Graph., 21:483–490. Google ScholarDigital Library
    4. Bojsen-Hansen, M., Li, H., and Wojtan, C. 2012. Tracking surfaces with evolving topology. ACM Trans. Graph., 31. Google ScholarDigital Library
    5. Carranza, J., Theobalt, C., Magnor, M. A., and Seidel, H.-P. 2003. Free-viewpoint video of human actors. ACM Trans. Graph., 22. Google ScholarDigital Library
    6. Casas, D., Richardt, C., Collomosse, J., Theobalt, C., and Hilton, A. 2015. 4D model flow: precomputed appearance alignment for real-time 4D video interpolation. Computer Graphics Forum, 34(7). Google ScholarDigital Library
    7. Casas, D., Tejera, M., Guillemaut, J.-Y., and Hilton, A. 2012. 4D parametric motion graphs for interactive animation. In Symp. on Interactive 3D Graphics and Games, pages 103–110. Google ScholarDigital Library
    8. Casas, D., Volino, M., Collomosse, J., and Hilton, A. 2014. 4D video textures for interactive character appearance. Comput. Graph. Forum, 33. Google ScholarDigital Library
    9. Chao, I., Pinkall, U., Sanan, P., and Schröder, P. 2010. A simple geometric model for elastic deformations. ACM Trans. Graph., 29. Google ScholarDigital Library
    10. Chuang, M., Luo, L., Brown, B., Rusinkiewicz, S., and Kazhdan, M. 2009. Estimating the Laplace-Beltrami operator by restricting 3D functions. Symposium on Geometry Processing. Google ScholarDigital Library
    11. Collet, A., Chuang, M., Sweeney, P., Gillett, D., Evseev, D., Calabrese, D., Hoppe, H., Kirk, A., and Sullivan, S. 2015. High-quality streamable free-viewpoint video. ACM Trans. Graph., 34. Google ScholarDigital Library
    12. de Goes, F., Desbrun, M., and Tong, Y. 2015. Vector field processing on triangle meshes. In SIGGRAPH Asia 2015 Courses, pages 17:1–17:48. Google ScholarDigital Library
    13. Dziuk, G. 1988. Finite elements for the Beltrami operator on arbitrary surfaces. In Partial Differential Equations and Calculus of Variations, Lecture Notes in Mathematics, volume 1357. Springer.Google Scholar
    14. Eisemann, M., De Decker, B., Magnor, M., Bekaert, P., De Aguiar, E., Ahmed, N., Theobalt, C., and Sellent, A. 2008. Floating textures. Computer Graphics Forum, 27(2).Google Scholar
    15. Funkhouser, T., Kazhdan, M., Shilane, P., Min, P., Kiefer, W., Tal, A., Rusinkiewicz, S., and Dobkin, D. 2004. Modeling by example. ACM Trans. Graph., 23(3). Google ScholarDigital Library
    16. Heck, R. and Gleicher, M. 2007. Parametric motion graphs. In Symposium on Interactive 3D Graphics and Games, ACM, pages 129–136. Google ScholarDigital Library
    17. Horn, B., Hilden, H., and Negahdaripour, S. 1988. Closed form solutions of absolute orientation using orthonormal matrices. Journal of the Optical Society, 5:1127–1135.Google ScholarCross Ref
    18. Huang, C.-H., Boyer, E., Navab, N., and Ilic, S. 2014. Human shape and pose tracking using keyframes. In Proc. CVPR. Google ScholarDigital Library
    19. Huang, P., Hilton, A., and Starck, J. 2009. Human motion synthesis from 3D video. In Proc. CVPR.Google Scholar
    20. Huang, P., Hilton, A., and Starck, J. 2010. Shape similarity for 3D video sequences of people. International Journal of Computer Vision, 89:362–381. Google ScholarDigital Library
    21. Huang, P., Tejera, M., Collomosse, J., and Hilton, A. 2015. Hybrid skeletal-surface motion graphs for character animation from 4D performance capture. ACM Trans. Graph., 34:17. Google ScholarDigital Library
    22. Jacobson, A., Panozzo, D., and others. 2016. libigl: A simple C++ geometry processing library. http://libigl.github.io/libigl/.Google Scholar
    23. Kanade, T., Rander, P., and Narayanan, P. J. 1997. Virtualized reality: Constructing virtual worlds from real scenes. IEEE Multimedia, 4. Google ScholarDigital Library
    24. Kazhdan, M. 2013. ShapeSPH. http://www.cs.jhu.edu/~misha/Code/ShapeSPH/ShapeAlign/.Google Scholar
    25. Kazhdan, M., Funkhouser, T., and Rusinkiewicz, S. 2003. Rotation invariant spherical harmonic representation of 3D shape descriptors. In Symposium on Geometry Processing. Google ScholarDigital Library
    26. Kovar, L., Gleicher, M., and Pighin, F. 2002. Motion graphs. ACM Trans. Graph., 21:473–482. Google ScholarDigital Library
    27. Lee, J., Chai, J., Reitsma, P. S., Hodgins, J. K., and Pollard, N. S. 2002. Interactive control of avatars animated with human motion data. ACM Trans. Graph., 21:491–500. Google ScholarDigital Library
    28. Levin, D. A., Peres, Y., and Wilmer, E. L. 2009. Markov chains and mixing times. American Mathematical Society.Google Scholar
    29. Li, H., Adams, B., Guibas, L. J., and Pauly, M. 2009. Robust single-view geometry and motion reconstruction. ACM Trans. Graph., 28. Google ScholarDigital Library
    30. Lucas, B. and Kanade, T. 1981. An iterative image registration technique with an application to stereo vision. In Proc. Intnl. Joint Conf. on Artificial Intelligence, pages 674–679. Google ScholarDigital Library
    31. Ovsjanikov, M., Ben-Chen, M., Solomon, J., Butscher, A., and Guibas, L. 2012. Functional maps: A flexible representation of maps between shapes. ACM Trans. Graph., 31. Google ScholarDigital Library
    32. Pinkall, U. and Polthier, K. 1993. Computing discrete minimal surfaces and their conjugates. Experimental Mathematics, 2.Google Scholar
    33. Prada, F. and Kazhdan, M. 2015. Unconditionally stable shock filters for image and geometry processing. Computer Graphics Forum, 34:201–210.Google ScholarDigital Library
    34. Rusinkiewicz, S. 2004. Trimesh v2. http://gfx.cs.princeton.edu/proj/trimesh2/.Google Scholar
    35. Shi, J. and Tomasi, C. 1994. Good features to track. In Proc. CVPR, pages 593–600.Google Scholar
    36. Shilane, P., Min, P., Kazhdan, M., and Funkhouser, T. 2004. The Princeton shape benchmark. In Shape Modeling International.Google Scholar
    37. Si, H. 2015. TetGen, a Delaunay-based quality tetrahedral mesh generator. ACM Trans. on Math. Software, 41. Google ScholarDigital Library
    38. Sorkine, O. and Alexa, M. 2007. As-rigid-as-possible surface modeling. In Symp. on Geometry Processing, pages 109–116. Google ScholarDigital Library
    39. Starck, J. and Hilton, A. 2007. CVSSP3D datasets. http://cvssp.org/data/cvssp3d/.Google Scholar
    40. Starck, J., Miller, G., and Hilton, A. 2005. Video-based character animation. In Symposium on Computer animation. Google ScholarDigital Library
    41. Tangelder, J. and Veltkamp, R. 2007. A survey of content based 3D shape retrieval methods. Multimedia Tools and Applications, 39:441–471. Google ScholarDigital Library
    42. Tomasi, C. and Kanade, T. 1991. Detection and tracking of point features. Technical Report CMU-CS-91-132.Google Scholar
    43. Vlasic, D., Peers, P., Baran, I., Debevec, P., Popović, J., Rusinkiewicz, S., and Matusik, W. 2009. Dynamic shape capture using multi-view photometric stereo. ACM Trans. Graph., 28. Google ScholarDigital Library
    44. Volino, M., Huang, P., and Hilton, A. 2015. Online interactive 4D character animation. In ACM SIGGRAPH Web3D Conference. Google ScholarDigital Library
    45. Von-Tycowicz, C., Schulz, C., Seidel, H.-P., and Hildebrandt, K. 2015. Real-time nonlinear shape interpolation. ACM Trans. Graph., 34. Google ScholarDigital Library
    46. Xu, F., Liu, Y., Stoll, C., Tompkin, J., Bharaj, G., Dai, Q., Seidel, H.-P., Kautz, J., and Theobalt, C. 2011. Video-based characters: Creating new human performances from a multi-view video database. ACM Trans. Graph., 30(4). Google ScholarDigital Library
    47. Zitnick, C. L., Kang, S. B., Uyttendaele, M., Winder, S., and Szeliski, R. 2004. High-quality video view interpolation using a layered representation. ACM Trans. Graph., 23. Google ScholarDigital Library
    48. Zollhöfer, M., Niessner, M., Izadi, S., Rehmann, C., Zach, C., Fisher, M., Wu, C., Fitzgibbon, A., Loop, C., Theobalt, C., and Stamminger, M. 2014. Real-time non-rigid reconstruction using an RGB-D camera. ACM Trans. Graph., 33. Google ScholarDigital Library

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