Abstract
Scalable Video Coding (SVC) uses a notion of layers within the encoded bitstream for providing temporal, spatial and quality scalability, separately or combined. By truncating layers the bitstream can be adapted to devices with different characteristics and to varying network constraints. Since the majority of the existing video content is encoded using H.264/AVC without scalability, they cannot benefit from these scalability tools, so a transcoding process should be applied to provide scalability to this existing encoded content. In this paper, an algorithm based on Machine Learning techniques for temporal scalability transcoding from H.264/AVC to SVC focusing on mode decision task is discussed. The results show that when our technique is applied, the complexity is reduced by 82% while maintaining coding efficiency.
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Garrido-Cantos, R., De Cock, J., Van Leuven, S., Cuenca, P., Garrido, A., Van de Walle, R. (2012). Fast Mode Decision Algorithm for H.264/AVC-to-SVC Transcoding with Temporal Scalability. 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_54
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DOI: https://doi.org/10.1007/978-3-642-27355-1_54
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