Highly Paralellized Architecture for Image Motion Estimation

  • Javier Díaz
  • Eduardo Ros
  • Sonia Mota
  • Rafael Rodriguez-Gomez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3985)


Optical flow computation is a well-known topic with a large number of contributions describing different models and their accuracies but real-time implementation of high frame-rate sequences remains as an open issue. The presented approach implements a novel superpipelined and fully parallelized architecture for optical flow processing with more than 70 pipelined stages that achieve a data throughput of one pixel per clock cycle. This customized DSP architecture is capable of processing up to 45 Mpixels/s arranged for example as 148 frames per second at VGA resolution (640x480 pixels). This is of extreme interest in order to use high frame-rate cameras for reliable motion processing. We justify the optical flow model chosen for the implementation, analyze the presented architecture and measure the system resource requirements. Finally, we evaluate the system comparing its performance with other previous approaches. To the best of our knowledge, the obtained performance is more than one range of magnitude higher than any previous real-time approach described in the literature.


Optical Flow Pipeline Stage FPGA Device Optical Flow Computation Optical Flow Estimation 
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.


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  1. 1.
    Barron, J.L., Fleet, D.J., Beauchemin, S.: Performance of optical-flow techniques. International Journal of Computer Vision 12(1), 43–77 (1994)CrossRefGoogle Scholar
  2. 2.
    McCane, B., Novins, K., Crannitch, D., Galvin, B.: On Benchmarking Optical Flow. Computer Vision and Image Understanding 84, 126–143 (2001)CrossRefzbMATHGoogle Scholar
  3. 3.
    Liu, H.C., Hong, T.S., Herman, M., Camus, T., Chellappa, R.: Accuracy vs. Efficiency Trade-offs in Optical Flow Algorithms. Computer Vision and Image Understanding 72(3), 271–286 (1998)CrossRefGoogle Scholar
  4. 4.
    Weber, J., Malik, J.: Robust computation of optical flow in a multi-scale differential framework. International Journal of Computer Vision 14, 67–81 (1995)CrossRefGoogle Scholar
  5. 5.
    Lim, S., Apostolopoulos, J.G., Gamal, A.E.: Optical flow estimation using temporally oversampled video. IEEE Transactions on Image Processing 14(8), 1074–1087 (2005)CrossRefGoogle Scholar
  6. 6.
    Lucas, B.D., Kanade, T.: An Iterative Image Registration Technique with an Application to Stereo Vision. In: Proc. of the DARPA Image Understanding Workshop, pp. 121–130 (1984)Google Scholar
  7. 7.
    Díaz, J., Ros, E., Mota, S., Carrillo, R., Agís, R.: Real time optical flow processing system. In: Becker, J., Platzner, M., Vernalde, S. (eds.) FPL 2004. LNCS, vol. 3203, pp. 617–626. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  8. 8.
    Díaz, J., Ros, E., Ortigosa, E.M., Mota, S.: FPGA based real-time optical-flow system. IEEE Transactions on Circuits and Systems for Video Technology (accepted for publication)Google Scholar
  9. 9.
    Bainbridge-Smith, A., Lane, R.G.: Determining Optical Flow Using a Differential Method. Image and Vision Computing 1, 11–22 (1997)CrossRefGoogle Scholar
  10. 10.
    Bainbridge-Smith, A., Lane, R.G.: Measuring Confidence in Optical Flow Estimation. IEE Electronic Letters 10, 882–884 (1996)CrossRefGoogle Scholar
  11. 11.
    Maya-Rueda, S., Arias-Estrada, M.: FPGA Processor for Real-Time Optical Flow Computation. In: Y. K. Cheung, P., Constantinides, G.A. (eds.) FPL 2003. LNCS, vol. 2778, pp. 1016–1103. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  12. 12.
    Brandt, J.W.: Improved Accuracy in Gradient Based Optical Flow Estimation. Int. Journal of Computer Vision 25(1), 5–22 (1997)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Simoncelli, E.P.: Design of multi-dimensional derivatives filters. In: Proc. IEEE International Conf. on Image Processing, Austin Tx, pp. 790–794 (1994)Google Scholar
  14. 14.
    Fleet, D.J., Langley, K.: Recursive filters for optical flow. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(1), 61–67 (1995)CrossRefGoogle Scholar
  15. 15.
    Bruhn, A., Weickert, J., Feddern, C., Kohlberger, T., Schnorr, C.: Variational optical flow computation in real time. IEEE Transactions on Image Processing 14(5), 608–615 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Dumontier, C., Luthon, F., Charras, J.P.: Real-time DSP implementation for MRF-based video motion detection. IEEE Transactions on Image Processing 8(10), 1341–1347 (1999)CrossRefGoogle Scholar
  17. 17.
    Forsell, M.J.: Architectural differences of efficient sequential and parallel computers. Journal of Systems Architecture: the EUROMICRO Journal 47(13), 1017–1041 (2002)CrossRefGoogle Scholar
  18. 18.
    SRAM ZBT memories, part number: 71T75602. Datasheet available at:
  19. 19.
    Celoxica company. Web site and products information available at:
  20. 20.
    Horn, B.K.P., Schunck, B.G.: Determining optical flow. Artificial Intelligent 17, 185–204 (1981)CrossRefGoogle Scholar
  21. 21.
    Martín, J.L., Zuloaga, A., Cuadrado, C., Lázaro, J., Bidarte, U.: Hardware implementation of optical flow constraint equation using FPGAs. Computer Vision and Image Understanding 3, 462–490 (2005)CrossRefGoogle Scholar
  22. 22.
    Niitsuma, H., Maruyama, T.: Real-Time Detection of Moving Objects. In: Becker, J., Platzner, M., Vernalde, S. (eds.) FPL 2004. LNCS, vol. 3203, pp. 1153–1157. Springer, Heidelberg (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Javier Díaz
    • 1
  • Eduardo Ros
    • 1
  • Sonia Mota
    • 2
  • Rafael Rodriguez-Gomez
    • 1
  1. 1.Dep. Arquitectura y Tecnología de ComputadoresUniversidad de GranadaSpain
  2. 2.Dep.Informática y Análisis NuméricoUniversidad de CórdobaSpain

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