DocumentCode :
2588529
Title :
Low-Complexity Heterogeneous Video Transcoding by Motion Vector Clustering
Author :
Shin, Yoonjeong ; Son, Namrye ; Toan, Nguyen Dinh ; Lee, Gueesang
Author_Institution :
Dept. of Comput. Eng., Gwangju Univ., Gwangju, South Korea
fYear :
2010
fDate :
21-23 April 2010
Firstpage :
1
Lastpage :
6
Abstract :
The recently developed video compression standard, H.264/AVC surpasses the performance of previous video standards, such as MPEG-2, MPEG-4(part2), and H.263 and is therefore expected to be selected as the video standard for most digital video applications. The widely distributed infrastructure, however, continues to use the previous standards. Heterogeneous video transcoding offers a significant key to the resolution of this problem. This paper suggests a new algorithm for H.264/AVC to MPEG-2 transcoding that uses motion vector clustering to reduce the computation time with no loss of quality. Such a clustering method can reduce the number of candidate motion vectors that are gathered during the H.264 decoding stage. These candidate motion vectors consider the correlation between the direction and distance of the motion vectors in the variable blocks in H.264/AVC. The candidate motion vector that has the least distortion is then selected in the MPEG-2 encoder. The MPEG-2 encoder can therefore use the best motion vector without carrying out computations for motion estimation. The experimental results show that the proposed method can maintain a good level of video quality while reducing the computational complexity by a considerable 64%, on average, compared to a cascade transcoder.
Keywords :
computational complexity; data compression; decoding; motion estimation; pattern clustering; transcoding; vectors; video coding; AVC; H.263; H.264 decoding; MPEG-2 encoder; MPEG-4; cascade transcoder; computational complexity; digital video; low complexity heterogeneous video transcoding; motion estimation; motion vector clustering; video compression; video quality; Automatic voltage control; Clustering algorithms; Clustering methods; Computational complexity; Decoding; Motion estimation; Standards development; Transcoding; Transform coding; Video compression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Applications (ICISA), 2010 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-5941-4
Electronic_ISBN :
978-1-4244-5943-8
Type :
conf
DOI :
10.1109/ICISA.2010.5480281
Filename :
5480281
Link To Document :
بازگشت