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Low-complexity transcoding algorithm from H.264/AVC to SVC using data mining

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Abstract
Nowadays, networks and terminals with diverse characteristics of bandwidth and capabilities coexist. To ensure a good quality of experience, this diverse environment demands adaptability of the video stream. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a low-complexity algorithm to convert an H.264/AVC bitstream without scalability to scalable bitstreams with temporal scalability in baseline and main profiles by accelerating the mode decision task of the scalable video coding encoding stage using machine learning tools. The results show that when our technique is applied, the complexity is reduced by 87% while maintaining coding efficiency.
Keywords
Scalable video coding, Low-complexity algorithms, H.264/AVC, Transcoding, STREAMS, ARCHITECTURES, VIDEO, Temporal scalability, Data mining

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MLA
Garrido-Cantos, Rosario et al. “Low-complexity Transcoding Algorithm from H.264/AVC to SVC Using Data Mining.” EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING (2013): n. pag. Print.
APA
Garrido-Cantos, Rosario, De Cock, J., Martínez, J. L., Van Leuven, S., Cuenca, P., & Garrido, A. (2013). Low-complexity transcoding algorithm from H.264/AVC to SVC using data mining. EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING.
Chicago author-date
Garrido-Cantos, Rosario, Jan De Cock, Jose Luis Martínez, Sebastiaan Van Leuven, Pedro Cuenca, and Antonio Garrido. 2013. “Low-complexity Transcoding Algorithm from H.264/AVC to SVC Using Data Mining.” Eurasip Journal on Advances in Signal Processing.
Chicago author-date (all authors)
Garrido-Cantos, Rosario, Jan De Cock, Jose Luis Martínez, Sebastiaan Van Leuven, Pedro Cuenca, and Antonio Garrido. 2013. “Low-complexity Transcoding Algorithm from H.264/AVC to SVC Using Data Mining.” Eurasip Journal on Advances in Signal Processing.
Vancouver
1.
Garrido-Cantos R, De Cock J, Martínez JL, Van Leuven S, Cuenca P, Garrido A. Low-complexity transcoding algorithm from H.264/AVC to SVC using data mining. EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING. 2013;
IEEE
[1]
R. Garrido-Cantos, J. De Cock, J. L. Martínez, S. Van Leuven, P. Cuenca, and A. Garrido, “Low-complexity transcoding algorithm from H.264/AVC to SVC using data mining,” EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2013.
@article{5647804,
  abstract     = {Nowadays, networks and terminals with diverse characteristics of bandwidth and capabilities coexist. To ensure a good quality of experience, this diverse environment demands adaptability of the video stream. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a low-complexity algorithm to convert an H.264/AVC bitstream without scalability to scalable bitstreams with temporal scalability in baseline and main profiles by accelerating the mode decision task of the scalable video coding encoding stage using machine learning tools. The results show that when our technique is applied, the complexity is reduced by 87% while maintaining coding efficiency.},
  articleno    = {82},
  author       = {Garrido-Cantos, Rosario and De Cock, Jan and Martínez, Jose Luis and Van Leuven, Sebastiaan and Cuenca, Pedro and Garrido, Antonio},
  issn         = {1687-6180},
  journal      = {EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING},
  keywords     = {Scalable video coding,Low-complexity algorithms,H.264/AVC,Transcoding,STREAMS,ARCHITECTURES,VIDEO,Temporal scalability,Data mining},
  language     = {eng},
  pages        = {24},
  title        = {Low-complexity transcoding algorithm from H.264/AVC to SVC using data mining},
  url          = {http://dx.doi.org/10.1186/1687-6180-2013-82},
  year         = {2013},
}

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