Have a personal or library account? Click to login

FPGA-Based Implementation of Real Time Optical Flow Algorithm and Its Applications for Digital Image Stabilization

Open Access
|Dec 2017

References

  1. S. Chhaniyara, P. Bunnun, L. Seneviratne and M. Ichikawa, “Optical Flow Algorith for Velocity Estimation of Ground Vehicles: A Feasibility Study”, International Journal on Smart Sensing and Intelligent Systems, Vol. 1, No. 1, March 2008.10.21307/ijssis-2017-289
  2. G. Barrows, C. Neely: “Mixed-mode VLSI optic flow sensors for inflight control of a micro air vehicle”, Proc. SPIE Vol. 4109, Critical Technologies for the Future of Computing; pp. 52-63, 2000.
  3. Diaz, J., Ros, E., Pelayo, F., Ortigosa, E. M., Mota, S.: “FPGA based realtime optical-flow system”; IEEE Transactions on Circuits and Systems for Video Technology, 16, 2 (2006), 274-279.
  4. B. McCane, K. Novins, D. Crannitch, and B. Galvin, “On benchmarking optical flow”, Comput. Vis. Image Understanding, vol. 84, pp. 126-143, 2001.10.1006/cviu.2001.0930
  5. Barron J. L, Fleet D. J, and Beauchemin S. S. , “Performance of optical flow techniques.” International Journal of Computer Vision, Vol. 12, pp. 43-77, 1994.10.1007/BF01420984
  6. B.D. Lucas and T. Kanade, “An Iterative Image Registration Technique with an Application to Stereo Vision (IJCAI),” Proceedings of the 7th International Joint Conference on Artificial Intelligence (IJCAI ‘81), April, 1981, pp. 674-679.
  7. Jangheon Kim, Thomas Sikora: “Hybrid recursive energy-based method for robust optical flow on large motion fields.”, ICIP (1) 2005: 129-13210.1109/ICIP.2005.1529704
  8. Bruhn, J. Weickert, C. Feddern, T. Kohlberger, C. Schnrr, “Real- Time Optic Flow Computation with Variational Methods”, CAIP 2003, LNCS, vol. 2756, pp. 222-229, 2003.
  9. P. Cobos and F. Monasterio, “FPGA implementation of the Horn & Schunck optical flow algorithm for motion detection in real time images”, Proc. DCIS’98 XIII, pp.616-621, 1998.
  10. S.J. Ko, S.H. Lee, and K.H. Lee, “Digital image stabilizing algorithms based on bit-plane matching”, IEEE Trans. Consumer Electron., vol. 44, no. 3, pp.796-800, Aug., 1998.10.1109/30.713172
  11. L. Xu and X. Lin, “Digital image stabilization based on circular block matching”, IEEE Transactions on Consumer Electronics, vol. 52, no. 2, pp. 566-574, 2006.10.1109/TCE.2006.1649681
  12. N. Ancona and T. Poggio, “Optical Flow from 1D Correlation: Application to a simple Time-To-Crash Detector”, Fourth International Conference on Computer Vision, IEEE Computer Society Press, May 11-14, 1993, Berlin, Germany, pp. 209-214.
  13. K. Janschek, V. Tchernykh, M. Beck: “Optical Flow based Navigation for Mobile Robots using an Embedded Optical Correlator”, Preprints of the 3rd IFAC Conference on Mechatronic Systems - Mechatronics 2004, 6-8 September 2004, Sydney, Australia, pp.793-798.
  14. P. C. Arribas and F. M. H. Maciá. FPGA implementation of the Horn & Shunk Optical Flow Algorithm for Motion Detection in real time Images. Proceedings of the XIII Design of Circuits and Integrated Systems Confer- ence, pages 616_621, 1998.
  15. S. Erturk, “Digital image stabilization with sub-image phase correlation based global motion estimation”, IEEE Trans. Consumer Electron., vol. 49, no. 4, pp.1320-1325, Nov., 2003.
  16. Intel Corporation, “Open Source Computer Vision Library”, Intel Corporation, http://developer.intel.com, 2000.
  17. Xilinx Company, “Virtex-II Pro and Virtex-II Pro X FPGA User Guide”, 2004.
  18. Z. Wei, D.-J. Lee, B. Nelson, James K. Archibald, and Barrett B. Edwards, “FPGA-Based Embedded Motion Estimation Sensor”, International Journal of Reconfigurable Computing Volume 2008 (2008).10.1155/2008/636145
  19. Z. Wei, D.-J. Lee, B. Nelson, and M. Martineau, “A fast and accurate tensor-based optical flow algorithm implemented in FPGA,” in Proceedings of the IEEE Workshop on Applications of Computer Vision (WACV ‘07), p. 18, Austin, Tex, USA, February 2007.10.1109/WACV.2007.5
  20. S. Baker, D. Scharstein, J.P. Lewis, S. Roth, M. J. Black, and R. Szeliski, “A Database and Evaluation Methodology for Optical Flow”, IEEE International Conference on Computer Vision, Oct. 2007.10.1109/ICCV.2007.4408903
Language: English
Page range: 253 - 272
Published on: Dec 12, 2017
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2017 Robert Piotrowski, Stanislaw Szczepanski, Slawomir Koziel, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.