Image and Video-Based Artistic Stylisation pp 285-308

Part of the Computational Imaging and Vision book series (CIVI, volume 42) | Cite as

Computer-Assisted Repurposing of Existing Animations

Chapter

Abstract

Despite the recent proliferation of modern 3D computer-generated imagery, the classical 2D hand-drawn style retains an important role in the field of cartoon animation. Although existing 3D modelling and animation tools open a vast pool of new possibilities, they still suffer from lack of expressiveness. This chapter presents a selection of advanced image processing techniques, the aim of which is to build a bridge between hand-drawn 2D animation and fully computer-assisted approaches. Tailored for usage in a real production pipeline, these techniques enable various complex manipulation and enhancement tasks such as colorization, 2D-to-3D conversion, example-based synthesis or rendering similar to 3D computer-generated imagery to be done with minimal user effort.

References

  1. 1.
    Alexa, M., Cohen-Or, D., Levin, D.: As-rigid-as-possible shape interpolation. In: ACM SIGGRAPH Conference Proceedings, pp. 157–164 (2000) Google Scholar
  2. 2.
    Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(24), 509–522 (2002) CrossRefGoogle Scholar
  3. 3.
    Boykov, Y., Funka-Lea, G.: Graph cuts and efficient N-D image segmentation. Int. J. Comput. Vis. 70(2), 109–131 (2006) CrossRefGoogle Scholar
  4. 4.
    Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE Trans. Pattern Anal. Mach. Intell. 26(9), 1124–1137 (2004) CrossRefGoogle Scholar
  5. 5.
    Boykov, Y., Veksler, O., Zabih, R.: Markov random fields with efficient approximations. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 648–655 (1998) Google Scholar
  6. 6.
    Dahlhaus, E., Johnson, D.S., Papadimitriou, C.H., Seymour, P.D., Yannakakis, M.: The complexity of multiway cuts. In: Proceedings of ACM Symposium on Theory of Computing, pp. 241–251 (1992) Google Scholar
  7. 7.
    Ecker, A., Jepson, A.D.: Polynomial shape from shading. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 145–152 (2010) Google Scholar
  8. 8.
    Felzenszwalb, P.F., Huttenlocher, D.P.: Distance transforms of sampled functions. Tech. Rep. TR2004-1963, Cornell University (2004) Google Scholar
  9. 9.
    Glocker, B., Komodakis, N., Tziritas, G., Navab, N., Paragios, N.: Dense image registration through MRFs and efficient linear programming. Med. Image Anal. 12(6), 731–741 (2008) CrossRefGoogle Scholar
  10. 10.
    Grady, L.: Random walks for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1768–1783 (2006) CrossRefGoogle Scholar
  11. 11.
    Igarashi, T., Moscovich, T., Hughes, J.F.: As-rigid-as-possible shape manipulation. ACM Trans. Graph. 24(3), 1134–1141 (2005) CrossRefGoogle Scholar
  12. 12.
    Jamriška, O., Sýkora, D., Hornung, A.: Cache-efficient graph cuts on structured grids. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 3673–3680 (2012) Google Scholar
  13. 13.
    Jeschke, S., Cline, D., Wonka, P.: A GPU Laplacian solver for diffusion curves and Poisson image editing. ACM Trans. Graph. 28(5), 116 (2009) Google Scholar
  14. 14.
    Johnston, S.F.: Lumo: illumination for cel animation. In: Proceedings of International Symposium on Non-photorealistic Animation and Rendering, pp. 45–52 (2002) CrossRefGoogle Scholar
  15. 15.
    Kahn, A.B.: Topological sorting of large networks. Commun. ACM 5(11), 558–562 (1962) MATHCrossRefGoogle Scholar
  16. 16.
    Kaneko, T., Takahei, T., Inami, M., Kawakami, N., Yanagida, Y., Maeda, T., Tachi, S.: Detailed shape representation with parallax mapping. In: Proceedings of International Conference on Artificial Reality and Telexistence, pp. 205–208 (2001) Google Scholar
  17. 17.
    Koenderink, J.J.: Pictorial relief. Philos. Trans. R. Soc. Lond. 356(1740), 1071–1086 (1998) MathSciNetMATHCrossRefGoogle Scholar
  18. 18.
    Koenderink, J.J., van Doorn, A.J., Kappers, A.M.L.: Pictorial surface attitude and local depth comparisons. Percept. Psychophys. 58(2), 163–173 (1996) CrossRefGoogle Scholar
  19. 19.
    Langer, M.S., Buelthoff, H.H.: Depth discrimination from shading under diffuse lighting. Perception 29(6), 649–660 (2000) CrossRefGoogle Scholar
  20. 20.
    Levin, A., Lischinski, D., Weiss, Y.: Colorization using optimization. ACM Trans. Graph. 23(3), 689–694 (2004) CrossRefGoogle Scholar
  21. 21.
    Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004) CrossRefGoogle Scholar
  22. 22.
    Luft, T., Colditz, C., Deussen, O.: Image enhancement by unsharp masking the depth buffer. ACM Trans. Graph. 25(3), 1206–1213 (2006) CrossRefGoogle Scholar
  23. 23.
    McCann, J., Pollard, N.S.: Local layering. ACM Trans. Graph. 28(3), 84 (2009) CrossRefGoogle Scholar
  24. 24.
    Orzan, A., Bousseau, A., Winnemöller, H., Barla, P., Thollot, J., Salesin, D.: Diffusion curves: a vector representation for smooth-shaded images. ACM Trans. Graph. 27(3), 92 (2008) CrossRefGoogle Scholar
  25. 25.
    Pao, H.K., Geiger, D., Rubin, N.: Measuring convexity for figure/ground separation. In: Proceedings of IEEE International Conference on Computer Vision, pp. 948–955 (1999) CrossRefGoogle Scholar
  26. 26.
    Potts, R.: Some generalized order-disorder transformation. In: Proceedings of Cambridge Philosophical Society, vol. 48, pp. 106–109 (1952) Google Scholar
  27. 27.
    Qu, Y., Wong, T.T., Heng, P.A.: Manga colorization. ACM Trans. Graph. 25(3), 1214–1220 (2006) CrossRefGoogle Scholar
  28. 28.
    Schaefer, S., McPhail, T., Warren, J.: Image deformation using moving least squares. ACM Trans. Graph. 25(3), 533–540 (2006) CrossRefGoogle Scholar
  29. 29.
    Shekhovtsov, A., Kovtun, I., Hlaváč, V.: Efficient MRF deformation model for non-rigid image matching. Comput. Vis. Image Underst. 112(1), 91–99 (2008) CrossRefGoogle Scholar
  30. 30.
    Sýkora, D., Buriánek, J., Žára, J.: Colorization of black-and-white cartoons. Image Vis. Comput. 23(9), 767–782 (2005) CrossRefGoogle Scholar
  31. 31.
    Sýkora, D., Buriánek, J., Žára, J.: Sketching cartoons by example. In: Proceedings of Eurographics Workshop on Sketch-Based Interfaces and Modeling, pp. 27–34 (2005) Google Scholar
  32. 32.
    Sýkora, D., Dingliana, J., Collins, S.: As-rigid-as-possible image registration for hand-drawn cartoon animations. In: Proceedings of International Symposium on Non-photorealistic Animation and Rendering, pp. 25–33 (2009) Google Scholar
  33. 33.
    Sýkora, D., Dingliana, J., Collins, S.: LazyBrush: flexible painting tool for hand-drawn cartoons. Comput. Graph. Forum 28(2), 599–608 (2009) CrossRefGoogle Scholar
  34. 34.
    Sýkora, D., Sedlacek, D., Jinchao, S., Dingliana, J., Collins, S.: Adding depth to cartoons using sparse depth (in)equalities. Comput. Graph. Forum 29(2), 615–623 (2010) CrossRefGoogle Scholar
  35. 35.
    Sýkora, D., Ben-Chen, M., Čadík, M., Whited, B., Simmons, M.: TexToons: practical texture mapping for hand-drawn cartoon animations. In: Proceedings of International Symposium on Non-photorealistic Animation and Rendering, pp. 75–83 (2011) Google Scholar
  36. 36.
    Walther, D., Koch, C.: Modeling attention to salient proto-objects. Neural Netw. 19(9), 1395–1407 (2006) MATHCrossRefGoogle Scholar
  37. 37.
    Wang, Y., Xu, K., Xiong, Y., Cheng, Z.Q.: 2D shape deformation based on rigid square matching. Comput. Animat. Virtual Worlds 19(3–4), 411–420 (2008) CrossRefGoogle Scholar
  38. 38.
    Winnemöller, H., Orzan, A., Boissieux, L., Thollot, J.: Texture design and draping in 2D images. Comput. Graph. Forum 28(4), 1091–1099 (2009) CrossRefGoogle Scholar
  39. 39.
    Yarbus, A.L.: Eye Movements and Vision. Plenum, New York (1967) Google Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.FEE, DCGICTU in PraguePraha 2Czech Republic
  2. 2.Trinity College DublinDublin 2Ireland

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