Skip to main content

A Duality Based Approach for Realtime TV-L 1 Optical Flow

  • Conference paper
Pattern Recognition (DAGM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4713))

Included in the following conference series:

Abstract

Variational methods are among the most successful approaches to calculate the optical flow between two image frames. A particularly appealing formulation is based on total variation (TV) regularization and the robust L 1 norm in the data fidelity term. This formulation can preserve discontinuities in the flow field and offers an increased robustness against illumination changes, occlusions and noise. In this work we present a novel approach to solve the TV-L 1 formulation. Our method results in a very efficient numerical scheme, which is based on a dual formulation of the TV energy and employs an efficient point-wise thresholding step. Additionally, our approach can be accelerated by modern graphics processing units. We demonstrate the real-time performance (30 fps) of our approach for video inputs at a resolution of 320×240 pixels.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alvarez, L., Weickert, J., Sánchez, J.: A scale-space approach to nonlocal optical flow calculations. In: Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision, pp. 235–246 (1999)

    Google Scholar 

  2. Anandan, P.: A computational framework and an algorithm for the measurement of visual motion. Int. J. Comput. Vision 2, 283–310 (1989)

    Article  Google Scholar 

  3. Aubert, G., Deriche, R., Kornprobst, P.: Computing optical flow via variational techniques. SIAM J. Appl. Math. 60(1), 156–182 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  4. Aujol, J.-F., Gilboa, G., Chan, T., Osher, S.: Structure-texture image decomposition–modeling, algorithms, and parameter selection. Int. J. Comput. Vision 67(1), 111–136 (2006)

    Article  Google Scholar 

  5. Black, M.J., Anandan, P.: A framework for the robust estimation of optical flow. In: ICCV 1993, pp. 231–236 (1993)

    Google Scholar 

  6. Bresson, X., Esedoglu, S., Vandergheynst, P., Thiran, J., Osher, S.: Fast Global Minimization of the Active Contour Snake Model. Journal of Mathematical Imaging and Vision (2007)

    Google Scholar 

  7. Brox, T., Bruhn, A., Papenberg, N., Weickert, J.: High accuracy optical flow estimation based on a theory for warping. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 25–36. Springer, Heidelberg (2004)

    Google Scholar 

  8. Bruhn, A., Weickert, J., Feddern, C., Kohlberger, T., Schnörr, C.: Variational optical flow computation in real time. IEEE Transactions on Image Processing 14(5), 608–615 (2005)

    Article  MathSciNet  Google Scholar 

  9. Bruhn, A., Weickert, J., Kohlberger, T., Schnörr, C.: A multigrid platform for real-time motion computation with discontinuity-preserving variational methods. Int. J. Comput. Vision 70(3), 257–277 (2006)

    Article  Google Scholar 

  10. Camus, T.A.: Real-time quantized optical flow. Journal of Real-Time Imaging, Special Issue on Real-Time Motion Analyis 3, 71–86 (1997)

    Google Scholar 

  11. Chambolle, A.: An algorithm for total variation minimization and applications. Journal of Mathematical Imaging and Vision 20(1–2), 89–97 (2004)

    MathSciNet  Google Scholar 

  12. Chan, T.F., Golub, G.H., Mulet, P.: A nonlinear primal-dual method for total variation-based image restoration. In: ICAOS 1996, Paris, 1996, vol. 219, pp. 241–252 (1996)

    Google Scholar 

  13. Horn, B.K.P., Schunck, B.G.: Determining optical flow. Artificial Intelligence 17, 185–203 (1981)

    Article  Google Scholar 

  14. Mémin, E., Pérez, P.: Hierarchical estimation and segmentation of dense motion fields. Int. J. Comput. Vision 46(2), 129–155 (2002)

    Article  MATH  Google Scholar 

  15. Nagel, H.-H., Enkelmann, W.: An investigation of smoothness constraints for the estimation of displacement vector fields from image sequences. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 8, 565–593 (1986)

    Article  Google Scholar 

  16. Papenberg, N., Bruhn, A., Brox, T., Didas, S., Weickert, J.: Highly accurate optic flow computation with theoretically justified warping. Int’l J. Computer Vision, 141–158 (2006)

    Google Scholar 

  17. Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Physica D 60, 259–268 (1992)

    Article  MATH  Google Scholar 

  18. Strzodka, R., Garbe, C.: Real-time motion estimation and visualization on graphics cards. In: IEEE Visualization 2004, pp. 545–552. IEEE Computer Society Press, Los Alamitos (2004)

    Chapter  Google Scholar 

  19. Weickert, J., Brox, T.: Diffusion and regularization of vector- and matrix-valued images. Inverse Problems, Image Analysis and Medical Imaging. Contemporary Mathematics 313, 251–268 (2002)

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Fred A. Hamprecht Christoph Schnörr Bernd Jähne

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zach, C., Pock, T., Bischof, H. (2007). A Duality Based Approach for Realtime TV-L 1 Optical Flow. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds) Pattern Recognition. DAGM 2007. Lecture Notes in Computer Science, vol 4713. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74936-3_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74936-3_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74933-2

  • Online ISBN: 978-3-540-74936-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics