Low-Complexity Coarse-Level Mode-Mapping Based H.264/AVC to H.264/SVC Spatial Transcoding for Video Conferencing

Lei SUN; Jie LENG; Jia SU; Yiqing HUANG; Hiroomi MOTOHASHI; Takeshi IKENAGA

doi:10.1587/transinf.E95.D.1313

Low-Complexity Coarse-Level Mode-Mapping Based H.264/AVC to H.264/SVC Spatial Transcoding for Video Conferencing

Lei SUN, Jie LENG, Jia SU, Yiqing HUANG, Hiroomi MOTOHASHI, Takeshi IKENAGA

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Scalable Video Coding (SVC) was standardized as an extension of H.264/AVC with the intention to provide flexible adaptation to heterogeneous networks and different end-user requirements, which provides great scalability in multi-point applications such as video conferencing. However, due to the existence of H.264/AVC-based systems, transcoding between AVC and SVC becomes necessary. Most existing works focus on temporal transcoding, quality transcoding or SVC-to-AVC spatial transcoding while the straightforward re-encoding method requires high computational cost. This paper proposes a low-complexity AVC-to-SVC spatial transcoder based on coarse-level mode mapping for video conferencing scenes. First, to omit unnecessary motion estimations (ME) for layers with reduced resolution, an ME skipping scheme based on AVC mode distribution is proposed with an adaptive search range. Then a probability-profile based scheme is proposed for further mode skipping. After that 3 coarse-level mode-mapping methods are presented for fast mode decision and the adaptive usage of the 3 methods is discussed. Finally, motion vector (MV) refinement is introduced for further lower-layer time reduction. As for the top layer, direct encapsulation is proposed to preserve better quality and another scheme involving inter-layer predictions is also provided for bandwidth-crucial applications. Simulation results show that proposed transcoder achieves up to 92.6% time reduction without significant coding efficiency loss compared to re-encoding method.

Publication: IEICE TRANSACTIONS on Information Vol.E95-D No.5 pp.1313-1323

Publication Date: 2012/05/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1587/transinf.E95.D.1313

Type of Manuscript: Special Section PAPER (Special Section on Recent Advances in Multimedia Signal Processing Techniques and Applications)

Category: Video Processing

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Lei SUN, Jie LENG, Jia SU, Yiqing HUANG, Hiroomi MOTOHASHI, Takeshi IKENAGA, "Low-Complexity Coarse-Level Mode-Mapping Based H.264/AVC to H.264/SVC Spatial Transcoding for Video Conferencing" in IEICE TRANSACTIONS on Information, vol. E95-D, no. 5, pp. 1313-1323, May 2012, doi: 10.1587/transinf.E95.D.1313.
Abstract: Scalable Video Coding (SVC) was standardized as an extension of H.264/AVC with the intention to provide flexible adaptation to heterogeneous networks and different end-user requirements, which provides great scalability in multi-point applications such as video conferencing. However, due to the existence of H.264/AVC-based systems, transcoding between AVC and SVC becomes necessary. Most existing works focus on temporal transcoding, quality transcoding or SVC-to-AVC spatial transcoding while the straightforward re-encoding method requires high computational cost. This paper proposes a low-complexity AVC-to-SVC spatial transcoder based on coarse-level mode mapping for video conferencing scenes. First, to omit unnecessary motion estimations (ME) for layers with reduced resolution, an ME skipping scheme based on AVC mode distribution is proposed with an adaptive search range. Then a probability-profile based scheme is proposed for further mode skipping. After that 3 coarse-level mode-mapping methods are presented for fast mode decision and the adaptive usage of the 3 methods is discussed. Finally, motion vector (MV) refinement is introduced for further lower-layer time reduction. As for the top layer, direct encapsulation is proposed to preserve better quality and another scheme involving inter-layer predictions is also provided for bandwidth-crucial applications. Simulation results show that proposed transcoder achieves up to 92.6% time reduction without significant coding efficiency loss compared to re-encoding method.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E95.D.1313/_p

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@ARTICLE{e95-d_5_1313,
author={Lei SUN, Jie LENG, Jia SU, Yiqing HUANG, Hiroomi MOTOHASHI, Takeshi IKENAGA, },
journal={IEICE TRANSACTIONS on Information},
title={Low-Complexity Coarse-Level Mode-Mapping Based H.264/AVC to H.264/SVC Spatial Transcoding for Video Conferencing},
year={2012},
volume={E95-D},
number={5},
pages={1313-1323},
abstract={Scalable Video Coding (SVC) was standardized as an extension of H.264/AVC with the intention to provide flexible adaptation to heterogeneous networks and different end-user requirements, which provides great scalability in multi-point applications such as video conferencing. However, due to the existence of H.264/AVC-based systems, transcoding between AVC and SVC becomes necessary. Most existing works focus on temporal transcoding, quality transcoding or SVC-to-AVC spatial transcoding while the straightforward re-encoding method requires high computational cost. This paper proposes a low-complexity AVC-to-SVC spatial transcoder based on coarse-level mode mapping for video conferencing scenes. First, to omit unnecessary motion estimations (ME) for layers with reduced resolution, an ME skipping scheme based on AVC mode distribution is proposed with an adaptive search range. Then a probability-profile based scheme is proposed for further mode skipping. After that 3 coarse-level mode-mapping methods are presented for fast mode decision and the adaptive usage of the 3 methods is discussed. Finally, motion vector (MV) refinement is introduced for further lower-layer time reduction. As for the top layer, direct encapsulation is proposed to preserve better quality and another scheme involving inter-layer predictions is also provided for bandwidth-crucial applications. Simulation results show that proposed transcoder achieves up to 92.6% time reduction without significant coding efficiency loss compared to re-encoding method.},
keywords={},
doi={10.1587/transinf.E95.D.1313},
ISSN={1745-1361},
month={May},}

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TY - JOUR
TI - Low-Complexity Coarse-Level Mode-Mapping Based H.264/AVC to H.264/SVC Spatial Transcoding for Video Conferencing
T2 - IEICE TRANSACTIONS on Information
SP - 1313
EP - 1323
AU - Lei SUN
AU - Jie LENG
AU - Jia SU
AU - Yiqing HUANG
AU - Hiroomi MOTOHASHI
AU - Takeshi IKENAGA
PY - 2012
DO - 10.1587/transinf.E95.D.1313
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2012
AB - Scalable Video Coding (SVC) was standardized as an extension of H.264/AVC with the intention to provide flexible adaptation to heterogeneous networks and different end-user requirements, which provides great scalability in multi-point applications such as video conferencing. However, due to the existence of H.264/AVC-based systems, transcoding between AVC and SVC becomes necessary. Most existing works focus on temporal transcoding, quality transcoding or SVC-to-AVC spatial transcoding while the straightforward re-encoding method requires high computational cost. This paper proposes a low-complexity AVC-to-SVC spatial transcoder based on coarse-level mode mapping for video conferencing scenes. First, to omit unnecessary motion estimations (ME) for layers with reduced resolution, an ME skipping scheme based on AVC mode distribution is proposed with an adaptive search range. Then a probability-profile based scheme is proposed for further mode skipping. After that 3 coarse-level mode-mapping methods are presented for fast mode decision and the adaptive usage of the 3 methods is discussed. Finally, motion vector (MV) refinement is introduced for further lower-layer time reduction. As for the top layer, direct encapsulation is proposed to preserve better quality and another scheme involving inter-layer predictions is also provided for bandwidth-crucial applications. Simulation results show that proposed transcoder achieves up to 92.6% time reduction without significant coding efficiency loss compared to re-encoding method.
ER -