Abstract
H.264/AVC is the most recent predictive video compression standard to outperform other existing video coding standards by means of higher computational complexity. In recent years, heterogeneous computing has emerged as a cost-efficient solution for high-performance computing. In the literature, several algorithms have been proposed to accelerate video compression, but so far there have not been many solutions that deal with video codecs using heterogeneous systems. This paper proposes an algorithm to perform H.264/AVC inter prediction. The proposed algorithm performs the motion estimation, both with full-pixel and sub-pixel accuracy, using CUDA to assist the CPU, obtaining remarkable time reductions while maintaining rate-distortion performance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
ISO/IEC International Standard 14496-10:2005, Information technology – Coding of audio-visual objects – Part 10: Advanced Video Coding
Wiegand, T., Sullivan, G.J., Bjontegaard, G., Luthra, A.: Overview of the H.264/AVC Video Coding Standard. IEEE Transaction on Circuits and System for Video Technology 13(7), 560–576 (2003)
Feng, W.-C., Manocha, D.: High-performance computing using accelerators. Parallel Computing 33(10-11), 645–647 (2007)
Nvidia, Nvidia CUDA Compute Unified Device Architecture-Programming Guide, Version 3.2 (August 2010)
Wiegand, T., Girod, B.: Lagrange multiplier selection in hybrid video coder control. In: Proc. IEEE International Conference on Image Processing, ICIP (2001)
Lee, C.-Y., Lin, Y.-C., Wu, C.-L., Chang, C.-H., Tsao, Y.-M., Chien, S.-Y.: Multi-Pass and Frame Parallel Algorithms of Motion Estimation in H.264/AVC for Generic GPU. In: Proceedings of IEEE International Conference on Multimedia and Expo 2007 (ICME 2007), Beijing (China), pp. 1603–1606 (July 2007)
Ryoo, S., Rodrigues, C., Baghsorkhi, S., Stone, S., Kirk, D., Hwu, W.-M.: Optimization Principles and Application Performance Evaluation of a Multithreaded GPU Using CUDA. In: Proceedings of the 13th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Salt Lake City (USA), pp. 73–82 (February 2008)
Chen, W.-N., Hang, H.-M.: H.264/AVC motion estimation implementation on Compute Unified Device Architecture (CUDA). In: Proceedings of IEEE International Conference on Multimedia and Expo 2008 (ICME 2008), Hannover (Germany), pp. 679–700 (June 2008)
Cheung, N.-M., Fan, X., Au, O.C., Kung, M.-C.: Video Coding on Multi-Core Graphics Processors. IEEE Signal Processing Magazine 27(2), 79–89 (2010)
Cheung, N.-M., Au, O.C., Kung, M.-C., Wong, P.H.W., Liu, C.H.: Highly Parallel Rate-Distortion Optimized Intra Mode Decision On Multi-Core Graphics Processors. IEEE Transactions on Circuit and System for Video Technology 19(11), 1692–1703 (2009)
Joint Video Team (JVT) of ISO/IEC MPEG and ITU-T VCEG, Reference Software to Committee Draft. JVT-F100 JM17.2 (2010)
X.264 reference software, http://www.videolan.org/developers/x264.html
Sullivan, G., Bjøntegaard, G.: Recommended Simulation Common Conditions for H.26L Coding Efficiency Experiments on Low-Resolution Progressive-Scan Source Material, ITU-T VCEG, Doc. VCEG-N81 (2001)
Richardson, I.E.G.: Video codec design, 2nd edn. John Willey & Sons LTD. (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rodríguez-Sánchez, R., Martínez, J.L., Fernández-Escribano, G., Sánchez, J.L., Claver, J.M. (2012). A Fast GPU-Based Motion Estimation Algorithm for H.264/AVC. In: Schoeffmann, K., Merialdo, B., Hauptmann, A.G., Ngo, CW., Andreopoulos, Y., Breiteneder, C. (eds) Advances in Multimedia Modeling. MMM 2012. Lecture Notes in Computer Science, vol 7131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27355-1_51
Download citation
DOI: https://doi.org/10.1007/978-3-642-27355-1_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27354-4
Online ISBN: 978-3-642-27355-1
eBook Packages: Computer ScienceComputer Science (R0)