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  •   University of Thessaly Institutional Repository
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  •   University of Thessaly Institutional Repository
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
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Coding Time Prediction in H.264/HEVC Transcoding Using Macroblock Sizes

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Author
Papadopoulos P.K., Panagou N., Koziri M., Kolomvatsos K., Loukopoulos T., Anagnostopoulos I.
Date
2019
Language
en
DOI
10.1109/SMAP.2019.8864805
Keyword
Codes (symbols)
Forecasting
Image coding
Motion Picture Experts Group standards
Semantics
Social networking (online)
H.264/AVC
HEVC
Macro block
Time predictions
Video-transcoding
Video signal processing
Institute of Electrical and Electronics Engineers Inc.
Metadata display
Abstract
The continuous customers' demand for higher resolution video led to the development of video coding standards that surpass the limitations of H.264/AVC. Prominent examples in this category include the High Efficiency Video Coding (HEVC) and AV1 which both nominally target at least 50% better compression rate compared to H.264/AVC. However, with a plethora of videos already existing in H.264/AVC format and the majority of cameras in use supporting the older standard, the need for efficient transcoding of H.264/AVC videos into newer standards, cannot be overlooked. Although a significant amount of research exists on fast transcoding of H.264/AVC sequences, most of the works have focused on speeding up block level encoding, usually by taking advantage of mode and motion information that is already contained in the compressed input stream. Nevertheless, equally important to reducing per block transcoding time, is the exploitation of parallelism. Towards this end, identifying in advance the most computationally demanding regions is a prerequisite for efficient resource allocation, especially in a heterogeneous computing environment. In this paper we study the potential of using Macroblock size to predict the most computationally demanding frame regions. Experiments with commonly used benchmark video sequences illustrate the merits of our approach. © 2019 IEEE.
URI
http://hdl.handle.net/11615/77622
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