Advertisement

Video Codec for Classical Cartoon Animations with Hardware Accelerated Playback

  • Daniel Sýkora
  • Jan Buriánek
  • Jiří Žára
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3804)

Abstract

We introduce a novel approach to video compression which is suitable for traditional outline-based cartoon animations. In this case the dynamic foreground consists of several homogeneous regions and the background is static textural image. For this drawing style we show how to recover hybrid representation where the background is stored as a single bitmap and the foreground as a sequence of vector images. This allows us to preserve compelling visual quality as well as spatial scalability even for low encoding bit-rates. We also introduce an efficient approach to play back compressed animations in real-time on commodity graphics hardware. Practical results confirm that for the same storage requirements our framework provides better visual quality as compared to standard video compression techniques.

Keywords

Visual Quality Video Compression Graphic Hardware Video Codec Background Layer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bancroft, D.J.: Advanced and economical telecine technology for global DTV production. In: Proceedings of Broadcast Engineering Conference (2000)Google Scholar
  2. 2.
    Sykes, P.J.: Digital Betacam: A new approach to broadcast digital recording. In: Proceedings of International Conference on Storage and Recording Systems, pp. 9–14 (1994)Google Scholar
  3. 3.
    Wong, A.H., Chen, C.: Comparison of ISO MPEG1 and MPEG2 video-coding standards. In: Proceedings of SPIE Visual Communications and Image Processing, vol. 2094, pp. 1436–1448 (1993)Google Scholar
  4. 4.
    Ebrahimi, T., Horne, C.: MPEG-4 natural video coding – An overview. Signal Processing: Image Communication 15, 365–385 (2000)CrossRefGoogle Scholar
  5. 5.
    Reid, M.M., Millar, R.J., Black, N.D.: Second-generation image coding: An overview. ACM Computing Surveys 29, 3–29 (1997)CrossRefGoogle Scholar
  6. 6.
    Clarke, R.J.: Image and video compression: A survey. International Journal of Imaging Systems and Technology 10, 20–32 (1999)CrossRefGoogle Scholar
  7. 7.
    Kwatra, V., Rossignac, J.: Space-time surface simplification and edgebreaker compression for 2D cel animations. International Journal on Shape Modeling 8, 119–137 (2002)zbMATHCrossRefGoogle Scholar
  8. 8.
    Ahmed, N., Natarajan, T., Rao, K.R.: Discrete cosine transform. IEEE Transactions on Computers C, 90–93 (1974)Google Scholar
  9. 9.
    Shapiro, J.M.: Embedded image coding using zerotrees of wavelet coefficients. IEEE Transactions on Signal Processing 41, 3445–3463 (1993)zbMATHCrossRefGoogle Scholar
  10. 10.
    Yang, Y., Galatsanos, N.P., Katsaggelos, A.K.: Projection-based spatially adaptive reconstruction of block-transform compressed images. IEEE Transactions on Image Processing 4, 896–908 (1995)CrossRefGoogle Scholar
  11. 11.
    Fan, G., Cham, W.K.: Model-based edge reconstruction for low bit-rate wavelet-compressed images. IEEE Transactions on Circuits and Systems for Video Technology 10, 120–132 (2000)CrossRefGoogle Scholar
  12. 12.
    Kwon, O., Chellappa, R.: Segmentation-based image compression. Optical Engeneering 7, 1581–1587 (1993)CrossRefGoogle Scholar
  13. 13.
    van Beek, P.J.L., Tekalp, A.M.: Object-based video coding using forward tracking 2-D mesh layers. In: Proceedings of SPIE Visual Communications and Image Processing, pp. 699–710 (1997)Google Scholar
  14. 14.
    Sýkora, D., Buriánek, J., Žára, J.: Segmentation of black and white cartoons. In: Proceedings of Spring Conference on Computer Graphics, pp. 245–254 (2003)Google Scholar
  15. 15.
    Sýkora, D., Buriánek, J., Žára, J.: Colorization of black-and-white cartoons. Image and Vision Computing 23, 767–852 (2005)CrossRefGoogle Scholar
  16. 16.
    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
  17. 17.
    Huertas, A., Medioni, G.: Detection of intensity changes with subpixel accuracy using Laplacian-Gaussian masks. IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 651–664 (1986)CrossRefGoogle Scholar
  18. 18.
    Odobez, J.M., Bouthemy, P.: Robust multiresolution estimation of parametric motion models. Journal of Visual Communication and Image Representation 6, 348–365 (1995)CrossRefGoogle Scholar
  19. 19.
    Wallace, G.K.: The JPEG still picture compression standard. Communications of the ACM 34, 30–44 (1991)CrossRefGoogle Scholar
  20. 20.
    Comaniciu, D., Meer, P.: Mean Shift: A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 603–619 (2002)CrossRefGoogle Scholar
  21. 21.
    Spaan, F., Lagendijk, R.L., Biermond, J.: Shape coding using polar coordinates and the discrete cosine transform. In: Proceedings of International Conference on Image Processing, pp. 516–519 (1997)Google Scholar
  22. 22.
    Zaletelj, J., Pecci, R., Spaan, F., Hanjalic, A., Lagendijk, R.L.: Rate distortion optimal contour compression using cubic B-splines. In: Proceedings of European Signal Processing Conference, pp. 1497–1500 (1998)Google Scholar
  23. 23.
    Weber, M.: AutoTrace: A utility for converting bitmap into vector graphics (2004), http://autotrace.sourceforge.net
  24. 24.
    Clark, J.H.: A fast scan-line algorithm for rendering parametric surfaces. IEEE Transactions on Image Processing 13, 289–299 (1979)Google Scholar
  25. 25.
    Burrows, M., Wheeler, D.J.: Block-sorting lossless data compression algorithm. Technical Report 124, SRC, Palo Alto, USA (1994)Google Scholar
  26. 26.
    Salomon, D.: Data compression: The complete reference. Springer, Heidelberg (1998)Google Scholar
  27. 27.
    Kuglin, C.D., Hines, D.C.: The phase correlation image alignment method. In: Proceedings of IEEE International Conference on Cybernetics and Society, pp. 163–165 (1975)Google Scholar
  28. 28.
    Borgefors, G.: Distance transformations in digital images. Computer Vision, Graphics, and Image Processing 34, 344–371 (1986)CrossRefGoogle Scholar
  29. 29.
    Frigo, M., Johnson, S.G.: FFTW: Library for computing the discrete Fourier transform (2005), http://www.fftw.org
  30. 30.
    Woo, M., Davis, T., Sheridan, M.B.: OpenGL Programming Guide: The Official Guide to Learning OpenGL. Addison-Wesley, Reading (1999)Google Scholar
  31. 31.
    Held, M.: FIST: Fast industrial-strength triangulation of polygons. Algorithmica 30, 563–596 (2001)zbMATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Daniel Sýkora
    • 1
  • Jan Buriánek
    • 1
  • Jiří Žára
    • 1
  1. 1.Digital Media ProductionCzech Technical University in Prague 

Personalised recommendations