Skip to main content
SpringerLink
Log in

Automatic MPEG-4 sprite coding—Comparison of integrated object segmentation algorithms

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Sprite coding, as standardized in MPEG-4 Visual, can result in superior performance compared to common hybrid video codecs. We consider sprite coding, which significantly increases the objective as well as the subjective quality of coded video content. The main challenge of this approach is the segmentation of the foreground objects in a preprocessing step. We evaluate automatic object segmentation methods based on global motion estimation and background sprite generation. The objects are coded using the MPEG-4 Visual Main Profile and compared with the Advanced Simple Profile.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

References

  1. Antonini M, Barlaud M, Mathieu P, Daubechies I (1992) Image coding using wavelet transform. IEEE Trans Image Process 1(2):205–220

    Article  Google Scholar 

  2. Baker S, Matthews I (2001) Equivalence and efficiency of image alignment algorithms. In: Computer vision and pattern recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE computer society conference, vol 1, pp I-1090–I-1097

  3. Baker S, Matthews I (2004) Lucas-Kanade 20 years on: a unifying framework. Int J Comput Vis 56(3):221–255

    Article  Google Scholar 

  4. Calderbank AR, Daubechies I, Sweldens W, Yeo B-L (1997) Lossless image compression using integer to integer wavelet transforms. In: Image processing, 1997. Proceedings, international conference on Oct 1997, vol 1, pp 596–599

  5. Daubechies I (1992) Ten lectures on wavelets. Society for Industrial Mathematics, Philadelphia

    MATH  Google Scholar 

  6. Dufaux F, Konrad J (2000) Efficient, robust, and fast global motion estimation for video coding. IEEE Trans Image Process 9(3):497–501

    Article  Google Scholar 

  7. Farin D (2005) Automatic video segmentation employing object/camera modeling techniques. Ph.D. thesis, Eindhoven University of Technology

  8. Farin D, de With PHN, Effelsberg W (2004) Minimizing MPEG-4 sprite coding-cost using multi-sprites. In: SPIE visual communications and image processing

  9. Farin D, de With PHN, Effelsberg WA (2004) Video-object segmentation using multi-sprite background subtraction. In: Multimedia and expo, 2004. ICME ’04. 2004 IEEE international conference, Jun 2004, vol 1, pp 343–346

  10. Farin D, Haller M, Krutz A, Sikora T (2008) Recent developments in panoramic image generation and sprite coding. In: Proc. IEEE 10th workshop on multimedia signal processing, Oct 2008, pp 64–69

  11. Fischler MA, Bolles RC (1981) Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun ACM 24(6):381–395

    Article  MathSciNet  Google Scholar 

  12. Haller M, Krutz A, Sikora T (2009) Evaluation of pixel- and motion vector-based global motion estimation for camera motion characterization. In: Proceedings of the international workshop on image analysis for multimedia interactive services (WIAMIS 2009). London, UK, ISBN 978-1-4244-3610-1, pp 49–52

  13. Krutz A, Frater M, Kunter M, Sikora T (2006) Windowed image registration for robust mosaicing of scenes with large background occlusions. In: Proc. IEEE international conference on image processing, Oct 2006, pp 353–356

  14. Krutz A, Glantz A, Frater M, Sikora T (2008) Local background sprite generation. In: International workshop on local and non-local approximation in image processing, LNLA 2008. IEEE, EURASIP, Tampere International Center for Signal Processing (TICSP), EUSIPCO2008, IEEE, EURASIP, Lausanne, Switzerland, Aug 2008

  15. Krutz A, Glantz A, Sikora T, Nunes P, Pereira F (2008) Automatic object segmentation algorithms for sprite coding using MPEG-4. In: Grgic S, Grgic M (ed) 50th international symposium ELMAR-2008, September, Proceedings, Zadar, Croatia, vol 2 of 2. Department of Wireless Communications, Faculty of Electrical Engineering and Computering, University of Zagreb, Croatia, ELMAR, Zadar, ELMAR, Croatian Society Electronics in Marine, Zadar, pp 459–462

  16. Krutz A, Glantz A, Borgmann T, Frater M, Sikora T (2009) Motion-based object segmentation using local background sprites. In: Proceedings of the IEEE international conference on acoustics, speech and signal processing (ICASSP 2009), Taipei, Taiwan, Apr 2009

  17. Krutz A, Kunter M, Dröse M, Frater M, Sikora T (2007) Content-adaptive video coding combining object-based coding and H.264/AVC. In: Picture coding symposium, Lisbon, Portugal, Nov 2007

  18. Krutz A, Kunter M, Sikora T, Mandal M, Frater M (2007) Motion-based object segmentation using sprites and anisotropic diffusion. In: Proc. eighth international workshop on image analysis for multimedia interactive services WIAMIS ’07, Jun 2007, pp 35–35

  19. Kunter M (2008) Advances in sprite-based video coding—towards universal usability. Ph.D. thesis, Technische Universität Berlin

  20. Kunter M, Krutz A, Mandal M, Sikora T (2007) Optimal multiple sprite generation based on physical camera parameter estimation. In: Visual communications and image processing, VCIP, electronic imaging 2007, San José, CA, USA, Jan 2007

  21. Kunter M, Krutz A, Dröse M, Frater M, Sikora T (2007) Object-based multiple sprite soding of unsegmented videos using H.264/AVC. In: IEEE int. conf. on image processing (ICIP 2007), San Antonio, Texas, USA, Sep 2007

  22. Lucas BD, Kanade T (1981) An iterative image registration technique with an application to stereo vision. In: International joint conference on artificial intelligence, Aug 1981, pp 674–679

  23. Mech R, Wollborn M (1997) A noise robust method for segmentation of moving objects in video sequences. In: Proc. IEEE international conference on acoustics, speech, and signal processing ICASSP-97, vol 4, pp 2657–2660

  24. Pereira F, Ebrahimi T (2002) The MPEG-4 book. Prentice Hall, Upper Saddle River

    Google Scholar 

  25. Perona P, Malik J (1990) Scale-space and edge detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell 12(7):629–639

    Article  Google Scholar 

  26. Sikora T (1997) The MPEG-4 video standard verification model. IEEE Trans Circuits Syst Video Technol 7(1):19–31

    Article  Google Scholar 

  27. Sikora T (2005) Trends and perspectives in image and video coding. In: Proc. of the IEEE, vol 93, pp 6–17

  28. Shi J, Tomasi C (1994) Good features to track. In: Proc. CVPR ’94. IEEE computer society conference on computer vision and pattern recognition, Jun 1994, pp 593–600

  29. Smolic A, Sikora T, Ohm J-R (1999) Long-term global motion estimation and its application for sprite coding, content description, and segmentation. IEEE Trans Circuits Syst Video Technol 9(8):1227–1242

    Article  Google Scholar 

  30. Tomasi C, Kanade T (1991) Detection and tracking of point features. Tech. Rep., Technical Report CMU-CS-91-132, Carnegie Mellon University, Apr 1991

  31. Wiegand T, Sullivan GJ, Bjontegaard G, Luthra A (2003) Overview of the H.264/AVC video coding standard. IEEE Trans Circuits Syst Video Technol 13(7):560–576

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Technische Universität Berlin, Communication Systems Group, Berlin, Germany

    Alexander Glantz, Andreas Krutz & Thomas Sikora

  2. Instituto Superior de Ciências do Trabalho e da Empresa, Instituto de Telecommunicações, Lisbon, Portugal

    Paulo Nunes

  3. Instituto Superior Técnico, Instituto de Telecommunicações, Lisbon, Portugal

    Fernando Pereira

Authors
  1. Alexander Glantz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andreas Krutz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Thomas Sikora
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Paulo Nunes
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fernando Pereira
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alexander Glantz.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Glantz, A., Krutz, A., Sikora, T. et al. Automatic MPEG-4 sprite coding—Comparison of integrated object segmentation algorithms. Multimed Tools Appl 49, 483–512 (2010). https://doi.org/10.1007/s11042-010-0469-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-010-0469-3

Keywords

Search

Navigation