Skip to main content
EURASIP Journal on Embedded Systems
Download PDF

Adaptive Motion Estimation Processor for Autonomous Video Devices

EURASIP Journal on Embedded Systems volume 2007, Article number: 057234 (2007) Cite this article

Abstract

Motion estimation is the most demanding operation of a video encoder, corresponding to at least 80% of the overall computational cost. As a consequence, with the proliferation of autonomous and portable handheld devices that support digital video coding, data-adaptive motion estimation algorithms have been required to dynamically configure the search pattern not only to avoid unnecessary computations and memory accesses but also to save energy. This paper proposes an application-specific instruction set processor (ASIP) to implement data-adaptive motion estimation algorithms that is characterized by a specialized datapath and a minimum and optimized instruction set. Due to its low-power nature, this architecture is highly suitable to develop motion estimators for portable, mobile, and battery-supplied devices. Based on the proposed architecture and the considered adaptive algorithms, several motion estimators were synthesized both for a Virtex-II Pro XC2VP30 FPGA from Xilinx, integrated within an ML310 development platform, and using a StdCell library based on a 0.18 μ m CMOS process. Experimental results show that the proposed architecture is able to estimate motion vectors in real time for QCIF and CIF video sequences with a very low-power consumption. Moreover, it is also able to adapt the operation to the available energy level in runtime. By adjusting the search pattern and setting up a more convenient operating frequency, it can change the power consumption in the interval between 1.6 mW and 15 mW.

[1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19]

References

  1. Pereira FCN, Ebrahimi T: The MPEG4 Book. Prentice Hall PTR, Upper Saddle River, NJ, USA; 2002.

    Google Scholar 

  2. Bhaskaran V, Konstantinides K: Image and Video Compression Standards: Algorithms and Architectures. 2nd edition. Kluwer Academic Publishers, Boston, Mass, USA; 1997.

    Book  Google Scholar 

  3. Pirsch P, Demassieux N, Gehrke W: VLSI architectures for video compression—a survey. Proceedings of the IEEE 1995,83(2):220-246. 10.1109/5.364465

    Article  Google Scholar 

  4. Dias T, Roma N, Sousa L: Efficient motion vector refinement architecture for sub-pixel motion estimation systems. Proceedings of IEEE Workshop on Signal Processing Systems Design and Implementation (SIPS '05), November 2005, Athens, Greece 313-318.

    Google Scholar 

  5. Li R, Zeng B, Liou ML: A new three-step search algorithm for block motion estimation. IEEE Transactions on Circuits and Systems for Video Technology 1994,4(4):438-442. 10.1109/76.313138

    Article  Google Scholar 

  6. Po L-M, Ma W-C: A novel four-step search algorithm for fast block motion estimation. IEEE Transactions on Circuits and Systems for Video Technology 1996,6(3):313-317. 10.1109/76.499840

    Article  Google Scholar 

  7. Zhu S, Ma K-K: A new diamond search algorithm for fast block-matching motion estimation. IEEE Transactions on Image Processing 2000,9(2):287-290. 10.1109/83.821744

    MathSciNet  Article  Google Scholar 

  8. Huang S-Y, Tsai W-C: A simple and efficient block motion estimation algorithm based on full-search array architecture. Signal Processing: Image Communication 2004,19(10):975-992. 10.1016/j.image.2004.08.001

    Google Scholar 

  9. Saponara S, Fanucci L: Data-adaptive motion estimation algorithm and VLSI architecture design for low-power video systems. IEE Proceedings Computers & Digital Techniques 2004,151(1):51-59. 10.1049/ip-cdt:20030858

    Article  Google Scholar 

  10. Tourapis AM, Au OC, Liou ML: Predictive motion vector field adaptive search technique (PMVFAST): enhancing block-based motion estimation. Proceedings of Visual Communications and Image Processing (VCIP '01), January 2001, San Jose, Calif, USA, Proceedings of SPIE 4310: 883-892.

    Google Scholar 

  11. Tourapis AM: Enhanced predictive zonal search for single and multiple frame motion estimation. Proceedings of Viual Communications and Image Processing (VCIP '02), January 2002, San Jose, Calif, USA, Proceedings of SPIE 4671: 1069-1079.

    Google Scholar 

  12. Ahmad I, Zheng W, Luo J, Liou M: A fast adaptive motion estimation algorithm. IEEE Transactions on Circuits and Systems for Video Technology 2006,16(3):420-438. 10.1109/TCSVT.2006.870022

    Article  Google Scholar 

  13. Momcilovic S, Dias T, Roma N, Sousa L: Application specific instruction set processor for adaptive video motion estimation. Proceedings of the 9th Euromicro Conference on Digital System Design: Architectures, Methods and Tools (DSD '06), August-September 2006, Dubrovnik, Croatia 160-167.

    Chapter  Google Scholar 

  14. Tuan J-C, Chang T-S, Jen C-W: On the data reuse and memory bandwidth analysis for full-search block-matching VLSI architecture. IEEE Transactions on Circuits and Systems for Video Technology 2002,12(1):61-72. 10.1109/76.981846

    Article  Google Scholar 

  15. Dias T, Roma N, Sousa L: Low power distance measurement unit for real-time hardware motion estimators. Proceedings of International Workshop on Power and Timing Modeling, Optimization and Simulation (PATMOS '06), September 2006, Montpellier, France 247-255.

    Google Scholar 

  16. Sousa L, Roma N: Low-power array architectures for motion estimation. Proceedings of IEEE International Workshop on Multimedia Signal Processing (MMSP '99), September 1999, Copenhagen, Denmark 679-684.

    Google Scholar 

  17. Xilinx Inc : User Guide. v1.1.1. ML310 User Guide for Virtex-II Pro Embedded Development Platform, October 2004

  18. Virtual Silicon Technology Inc : eSi-Route/11TM high performance standard cell library (UMC 0.18 μ m). Tech. Rep. v2.4. 2001.

    Google Scholar 

  19. Berić A, Sethuraman R, Peters H, van Meerbergen J, de Haan G, Pinto CA: A 27 mW 1.1 mm2 motion estimator for picture-rate up-converter. Proceedings of the 17th International Conference on VLSI Design (VLSI '04), January 2004, Mumbai, India 17: 1083-1088.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. INESC-ID/IST/ISEL, Rua Alves Redol 9, Lisboa, 1000-029, Portugal

    T Dias, S Momcilovic, N Roma & L Sousa

Authors
  1. T Dias
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S Momcilovic
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. N Roma
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. L Sousa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to T Dias.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Dias, T., Momcilovic, S., Roma, N. et al. Adaptive Motion Estimation Processor for Autonomous Video Devices. J Embedded Systems 2007, 057234 (2007). https://doi.org/10.1155/2007/57234

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1155/2007/57234

Keywords

  • Motion Estimation
  • Search Pattern
  • Motion Estimator
  • ASIP
  • Estimate Motion Vector