This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Power and Performance Analysis of Motion Estimation Based on Hardware and Software Realizations
June 2005 (vol. 54 no. 6)
pp. 714-726
Motion estimation is the most computationally expensive task in MPEG-style video compression. Video compression is starting to be widely used in battery-powered terminals, but surprisingly little is known about the power consumption of modern motion estimation algorithms. This paper describes our effort to analyze the power and performance of realistic motion estimation algorithms in both hardware and software realizations. For custom hardware realizations, this paper presents a general model of VLSI motion estimation architectures. This model allows us to analyze in detail the power consumption of a large class of modern motion estimation engines that can execute the motion estimation algorithms of interest to us. We compare these algorithms in terms of their power consumption and performance. For software realizations, this paper provides the first detailed instruction-level simulation results on motion estimation based on a programmable CPU core. We analyzed various aspects of the selected motion estimation algorithms, such as search speed and power distribution. This paper provides a guideline to two types of machine designs for motion estimation: custom ASIC (Application Specific Integrated Circuit) design and custom ASIP (Application Specific Instruction-set Processor) designs.

[1] K. Guttag, R.J. Gove, and J.R. V. Aken, “A Single Chip Multiprocessor for Multimedia: The mvp,” IEEE Computer Graphics and Applications, pp. 53-64, Nov. 1992.
[2] F. Catthoor, S. Wuytack, E.D. Greef, F. Balasa, L. Nachtergaele, and A. Vandecappelle, Custom Memory Management Methodology. Boston: Kluwer Academic, 1998.
[3] M.J. Chen, L.G. Chen, and T.D. Chiueh, “One-Dimensional Full Search Motion Estimation Algorithm for Video Coding,” IEEE Trans. Circuits and Systems for Video Technology, vol. 4, no. 5, pp. 504-509, Oct. 1994.
[4] T. Koga, K. Iinuma, A. Hirano, Y. Iijima, and T. Ishiguro, “Motion Compensated Interframe Coding for Video Conferencing,” Proc. Nat'l Telecomm. Conf., pp. 531-535, Nov. 1981.
[5] L.-P. Chau and X. Jing, “Efficient Three-Step Search Algorithm for Block Motion Estimation in Video Coding,” Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing 2003 (ICASSP '03), pp. 421-424, Apr. 2003.
[6] R. Li, B. Zeng, and M.L. Liou, “A New Three-Step Search Algorithm for Block Motion Estimation,” IEEE Trans. Circuits and Systems for Video Technology, vol. 4, no. 4, pp. 438-442, Aug. 1994.
[7] L.-M. Po and W.-C. Ma, “A Novel Four-Step Search Algorithm for Fast Block Motion Estimation,” IEEE Trans. Circuits and Systems for Video Technology, vol. 6, no. 3, pp. 313-317, June 1996.
[8] K.-T. Wang and O.T.-C. Chen, “Motion Estimation Using an Efficient Four-Step Search Method,” Proc. 1998 IEEE Int'l Symp. Circuits and Systems 1998 (ISCAS '98), pp. 217-220, June 1998.
[9] J.Y. Tham, S. Ranganath, M. Ranganath, and A.A. Kassim, “A Novel Unrestricted Center-Biased Diamond Search Algorithm for Block Motion Estimation,” IEEE Trans. Circuits and Systems for Video Technology, vol. 8, no. 4, pp. 369-377, Aug. 1998.
[10] S. Zhu and K.-K. Ma, “A New Diamond Search Algorithm for Fast Block-Matching Motion Estimation,” IEEE Trans. Image Processing, vol. 9, no. 2, pp. 287-290, Feb. 2000.
[11] C.-H. Cheung and L.-M. Po, “A Novel Cross-Diamond Search Algorithm for Fast Block Motion Estimation,” IEEE Trans. Circuits and Systems for Video Technology, vol. 12, no. 12, pp. 1168-1177, Dec. 2002.
[12] C. Cheung and L.M. Po, “A Novel Rood-Diamond Search Algorithm for Fast Block Motion Estimation,” Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing, pp. 3397-3400, May 2002.
[13] C. Zhu, X. Lin, L.P. Chau, H.A. Ang, and C.Y. Ong, “An Optimized Diamond Search Algorithm for Block Motion Estimation,” Proc. IEEE Intl Symp. Circuits and Systems, pp. 488-491, May 2002.
[14] S. Kappagantula and K.R. Rao, “Motion Compensated Predictive Interframe Coding,” IEEE Trans. Comm., vol. 33, no. 9, pp. 1011-1015, Sept. 1985.
[15] B. Liu and A. Zaccarin, “New Fast Algorithms for the Estimation of Block Motion Vectors,” IEEE Trans. Circuits and Systems for Video Technology, vol. 3, no. 2, pp. 148-157, Apr. 1993.
[16] “Simplescalar,” http:/www.simplescalar.com, 2004.
[17] “Simplepower,” http://www.cse.psu.edu/mdlsoftware.htm, 2002.

Index Terms:
Motion estimation algorithm, power modeling, performance optimization.
Citation:
Shengqi Yang, Wayne Wolf, N. Vijaykrishnan, "Power and Performance Analysis of Motion Estimation Based on Hardware and Software Realizations," IEEE Transactions on Computers, vol. 54, no. 6, pp. 714-726, June 2005, doi:10.1109/TC.2005.102
Usage of this product signifies your acceptance of the Terms of Use.