• DocumentCode
    3264765
  • Title

    Parallel rate-distortion optimised fast motion estimation algorithm for H.264/AVC using GPU

  • Author

    Shahid, M. Usman ; Ahmed, Arif ; Magli, Enrico

  • Author_Institution
    Dept. of Electron. & Telecommun., Politec. di Torino, Turin, Italy
  • fYear
    2013
  • fDate
    8-11 Dec. 2013
  • Firstpage
    221
  • Lastpage
    224
  • Abstract
    Recently, the parallel processing capability of the Graphics Processing Unit (GPU) has been employed for accelerating motion estimation in H.264/AVC encoder implementations. However, while implementing parallel motion estimation on GPU, the bit rate cost of the motion vector is generally ignored. This is due to the unavailability of the spatially predicted motion vectors, which leads to rate-distortion performance degradation. This paper presents a fast parallel motion estimation algorithm implemented on GPU using OpenCL to tackle this problem. The predicted motion vectors are estimated from temporally predicted motion vectors and used for evaluating the bit rate cost of the motion vectors simultaneously. The experimental results show that the proposed scheme achieves significant speedup and has comparable rate-distortion performance with respect to sequential fast motion estimation algorithm.
  • Keywords
    graphics processing units; motion estimation; parallel processing; rate distortion theory; video coding; GPU; H.264-AVC encoder implementations; OpenCL; graphics processing unit; motion vector prediction estimation; parallel processing capability; parallel rate-distortion optimised fast motion estimation algorithm; rate-distortion performance degradation; video coding; Bit rate; Graphics processing units; Motion estimation; Parallel processing; Prediction algorithms; Vectors; Video coding; GPU; H.264/AVC; OpenCL; motion estimation; video coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Picture Coding Symposium (PCS), 2013
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    978-1-4799-0292-7
  • Type

    conf

  • DOI
    10.1109/PCS.2013.6737723
  • Filename
    6737723