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25th IEEE/ACM International Symposium on Quality of Service (IWQoS)

作者： Zhu, Yifei Liu, Jiangchuan Simon Fraser Univ Sch Comp Sci Burnaby BC Canada South China Agr Univ Coll Nat Resources & Environm Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538627044

Live video contents in crowdsourced live streaming services are transcoded into multiple quality versions to better service viewers with different network and device configurations. Cloud computing becomes a natural choice to handle this transcoding service due to its elasticity and significant computational power. However, given the huge concurrent channel numbers in this crowdsourced live streaming service, even the cloud becomes significantly expensive for providing transcoding services to the whole community. In this poster, after observing that abundant computational resources reside in end viewers, we propose a Cloud-Crowd collaborative system, C2, which incentivizes idle end-viewers to join with the cloud to do video transcoding. Specifically, we propose an auction mechanism to carefully select stable viewers and determine the proper payment for them. Desirable economic properties, like incentive compatibility, can be achieved in our mechanism. Large-scale trace-driven simulations further demonstrate the superiority of our mechanisms in cost reduction and service stability.

关键词： transcoding Streaming media Cloud computing Stability analysis Uncertainty Collaboration Resource management

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transcoding method from H.264/AVC to high efficiency video coding based on similarity of intraprediction, interprediction, and motion vector

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JOURNAL OF ELECTRONIC IMAGING 2016年第5期25卷 53028.1-53028.1页

作者： Liu, Mei-Feng Zhong, Guo-Yun He, Xiao-Hai Qing, Lin-Bo East China Inst Technol Sch Mech & Elect Engn Nanchang 330013 Peoples R China East China Inst Technol Coll Informat Engn Nanchang 330013 Peoples R China Sichuan Univ Coll Elect & Informat Engn Chengdu 610065 Peoples R China

Currently, most video resources on line are encoded in the H.264/AVC format. More fluent video transmission can be obtained if these resources are encoded in the newest international video coding standard: high efficiency video coding (HEVC). In order to improve the video transmission and storage on line, a transcoding method from H.264/AVC to HEVC is proposed. In this transcoding algorithm, the coding information of intraprediction, interprediction, and motion vector (MV) in H.264/AVC video stream are used to accelerate the coding in HEVC. It is found through experiments that the region of interprediction in HEVC overlaps that in H.264/AVC. Therefore, the intraprediction for the region in HEVC, which is interpredicted in H.264/AVC, can be skipped to reduce coding complexity. Several macroblocks in H.264/AVC are combined into one PU in HEVC when the MV difference between two of the macroblocks in H.264/AVC is lower than a threshold. This method selects only one coding unit depth and one prediction unit (PU) mode to reduce the coding complexity. An MV interpolation method of combined PU in HEVC is proposed according to the areas and distances between the center of one macroblock in H.264/AVC and that of the PU in HEVC. The predicted MV accelerates the motion estimation for HEVC coding. The simulation results show that our proposed algorithm achieves significant coding time reduction with a little loss in bitrates distortion rate, compared to the existing transcoding algorithms and normal HEVC coding. (C) 2016 SPIE and IS&T

关键词： H264/AVC HEVC transcoding

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Scheduling Heuristics for Live Video transcoding on Cloud Edges

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ZTE Communications 2017年第2期15卷 35-41页

作者： Panagiotis Oikonomou Maria G. Koziri Nikos Tziritas Thanasis Loukopoulos XU Cheng-Zhong University of Thessaly Lamia 35100 Greece Research Center for Cloud Computing Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China

Efficient video delivery involves the transcoding of the original sequence into various resolutions,bitrates and standards,in order to match viewers’*** video coding and transcoding are computationally demanding,performing a portion of these tasks at the network edges promises to decrease both the workload and network traffic towards the data centers of media *** by the increasing popularity of live casting on social media platforms,in this paper we focus on the case of live video ***,we investigate scheduling heuristics that decide on which jobs should be assigned to an edge minidatacenter and which to a backend *** simulation experiments with different Qo S requirements we conclude on the best alternative.

关键词： video transcoding edge computing scheduling heuristics x264

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Machine learning based fast H.264/AVC to HEVC transcoding exploiting block partition similarity

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2016年第Jul.期38卷 824-837页

作者： Zhu, Linwei Zhang, Yun Li, Na Jiang, Gangyi Kwong, Sam Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China City Univ Wong Kong Dept Comp Sci Hong Kong Hong Kong Peoples R China Ningbo Univ Fac Informat Sci & Engn Ningbo 315211 Zhejiang Peoples R China City Univ Hong Kong Shenzhen Res Inst Shenzhen Peoples R China

Video transcoding is to convert one compressed video stream to another. In this paper, a fast H.264/AVC to High Efficiency Video Coding (HEVC) transcoding method based on machine learning is proposed by considering the similarity between compressed streams, especially the block partition correlations, to reduce the computational complexity. This becomes possible by constructing three-level binary classifiers to predict quad-tree Coding Unit (CU) partition in HEVC. Then, we propose a feature selection algorithm to get representative features to improve predication accuracy of the classification. In addition, we propose an adaptive probability threshold determination scheme to achieve a good trade-off between low coding complexity and high compression efficiency during the CU depth prediction in HEVC. Extensive experimental results demonstrate the proposed transcoder achieves complexity reduction of 50.2% and 49.2% on average under lowdelay P main and random access configurations while the rate distortion degradation is negligible. The proposed scheme is proved more effective as comparing with the state-of-the-art benchmarks. (C) 2016 Elsevier Inc. All rights reserved.

关键词： H.264/AVC High Efficiency Video Coding transcoding Machine learning Block partition similarity Feature selection

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FITD: Fast Intra transcoding from H.264/AVC to high efficiency video coding based on DCT coefficients and prediction modes

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2016年 38卷 130-140页

作者： Lin, Chow-Sing Yang, Wei-jong Su, Chieh-Wei Natl Univ Tainan Dept Comp Sci & Informat Engn 33Sec 2Shu Lin St Tainan 70005 Taiwan

In the literatures, the designs of H.264 to High Efficiency Video Coding (HEVC) transcoders mostly focus on inter transcoding. In this paper, a fast intra transcoding system from H.264 to HEVC based on discrete cosine transform (DCT) coefficients and intra prediction modes, called FITD, is proposed by using the intra information retrieved from an H.264 decoder for transcoding. To design effective transcoding strategies, FITD not only refers block size of intra prediction and intra prediction modes, but also effectively uses the DCT coefficients to help a transcoder to predict the complexity of the blocks. We successfully use DCT coefficients as well as intra prediction information embedded in H.264 bitstreams to predict the coding depth map for depth limitation and early termination to simplify HEVC re-encoding process. After a HEVC encoder gets the prediction of a certain CU size from depth map, if it reaches the predicted depth, the HEVC encoder will stop the next CU branch. As a result, the numbers of CU branches and predictions in HEVC re-encoder will be substantially reduced to achieve fast and precise intra transcoding. The experimental results show that the FITD is 1.7-2.5 times faster than the original HEVC in encoding intra frames, while the bitrate is only increased to 3% or less and the PSNR degradation is also controlled within 0.1 dB. Compared to the previous H.264 to HEVC transcoding approaches, FITD clearly maintains the better trade-off between re-encoding speed and video quality. (C) 2016 Elsevier Inc. All rights reserved.

关键词： HEVC transcoding Depth limitation Early termination Intra prediction

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Low-complexity heterogeneous architecture for H.264/HEVC video transcoding

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JOURNAL OF REAL-TIME IMAGE PROCESSING 2016年第2期12卷 311-327页

作者： Jesus Diaz-Honrubia, Antonio Cebrian-Marquez, Gabriel Luis Martinez, Jose Cuenca, Pedro Miguel Puerta, Jose Antonio Gamez, Jose Univ Castilla La Mancha Albacete Res Inst Informat I3A Albacete 02071 Spain

High efficiency video coding (HEVC) was developed by the Joint Collaborative Team on video coding to replace the current H.264/AVC standard, which has been widely adopted over the last few years. Therefore, there is a lot of legacy content encoded with H.264/AVC, and an efficient conversion to HEVC is needed. This paper presents a hybrid transcoding algorithm which makes use of soft computing techniques as well as parallel processing. On the one hand, a fast quadtree level decision algorithm tries to exploit the information gathered at the H.264/AVC decoder to make faster decisions on coding unit splitting in HEVC using a Na < ve-Bayes probabilistic classifier that is determined by a supervised data mining process. On the other hand, a parallel HEVC-encoding algorithm makes use of a heterogeneous platform composed of a multi-core central processing unit plus a graphics processing unit (GPU). In this way, from a coarse point of view, groups of frames or rows of a frame (both options are possible) are divided into threads to be executed on each core (each of which executes one of the aforementioned classifiers) and, from a finer point of view, all these threads work in a collaborative way on a single GPU to perform the motion estimation process on the co-processor. Experimental results show that the proposed transcoder can achieve a good tradeoff between coding efficiency and complexity compared with the anchor transcoder.

关键词： HEVC H.264/AVC transcoding Heterogeneous computing CTU splitting

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Spatially misaligned HEVC transcoding with computational-complexity scalability

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2016年第PartA期40卷 149-158页

作者： De Praeter, Johan Van Wallendael, Glenn Vermeir, Thijs Slowack, Jurgen Lambert, Peter Ghent Univ iMinds Data Sci Lab Sint Pietersnieuwstr 41 B-9000 Ghent Belgium Barco NV President Kennedypk 35 B-8500 Kortrijk Belgium

In control rooms, video walls display footage from multiple sources. Often, a composition of these sources is sent to other devices in a single video stream. To minimize the computational complexity of this composition process, information from the original bitstreams can be reused. However, in High Efficiency Video Coding (HEVC), simply copying the original encoding decisions is not compression efficient if the individual videos are spatially misaligned with the grid of coded blocks of the composition. Our proposed HEVC-based transcoder reduces the computational complexity by predicting encoding decisions of misaligned sequences by using a trivial method or a more adaptive, computational complexity scalable machine learning method. Higher compression efficiency is observed when more alignment is preserved with the original block grid. Overall, the machine learning method achieves a higher compression efficiency than the trivial method. Both methods attain a complexity reduction of up to 82% compared to the reference software. (C) 2016 Elsevier Inc. All rights reserved.

关键词： High Efficiency Video Coding (HEVC) Machine learning transcoding Picture composition

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Adaptive Fast Quadtree Level Decision Algorithm for H.264 to HEVC Video transcoding

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2016年第1期26卷 154-168页

作者： Jesus Diaz-Honrubia, Antonio Luis Martinez, Jose Cuenca, Pedro Antonio Gamez, Jose Miguel Puerta, Jose Univ Castilla La Mancha High Performance Networks & Architectures Grp Albacete 13071 Spain Univ Castilla La Mancha Intelligent Syst & Data Min Grp Albacete 13071 Spain

High Efficiency Video Coding (HEVC) was developed by the Joint Collaborative Team on Video Coding to replace the current H.264/Advanced Video Coding (AVC) standard, which has dominated digital video services in all segments of the domestic and professional markets for over ten years. Therefore, there is a lot of legacy content encoded with H.264/AVC, and an efficient video transcoding from H.264/AVC to HEVC will be needed to enable gradual migration to HEVC. In terms of rate-distortion (RD) performance, HEVC roughly doubles the RD compression performance of H.264/AVC at the expense of a high computational cost. HEVC adopts a quadtree-based coding unit (CU) block partitioning structure that is flexible in adapting various texture characteristics of images. However, this causes a dramatic increase in computational complexity due to the necessity of finding the best CU partitions. This paper presents an adaptive fast quadtree level decision algorithm that is designed to exploit the information gathered at the H.264/AVC decoder in order to make faster decisions on CU splitting in HEVC using a Naive-Bayes probabilistic classifier that is determined by a supervised data mining process. The experimental results show that the proposed algorithm can achieve a good tradeoff between coding efficiency and complexity compared with the anchor transcoder;moreover, it outperforms other related works available in the literature.

关键词： Coding unit (CU) splitting H.264/Advanced Video Coding (AVC) High Efficiency Video Coding (HEVC) software partitioning transcoding

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A distributed transcoding and content protection system Enabling pay per quality using the cloud

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TELECOMMUNICATION SYSTEMS 2016年第1期61卷 59-76页

作者： Diaz-Sanchez, Daniel Sanchez-Guerrero, Rosa Arias, Patricia Almenarez, Florina Marin, Andres Univ Carlos III Madrid Avda Univ 30 Leganes 28911 Spain Telefonica Espana Calle Gran Via 28 Madrid Spain

Video coding is a process for adapting media content to the constraints of transmission networks delivery and terminal device visualization. Moreover, content protection is also necessary. Nowadays the heterogeneity of client devices is increasing leading to different resolutions, qualities and form factors. Due to this, transcoding and protection are essential processes to be conducted in modern video distribution networks to adapt video to devices and network constraints and to enable pay per quality schemas enforcing content licenses. Unfortunately, transcoding and protection can be no longer considered linear since every single content should be transcoded in several formats and sometimes protected, so it would require a long time to finish. Modern scalable coding techniques, as H264 SVC, can help to save processing power and bandwidth providing in a single stream several video versions. However, if the enhancements of a SVC encoded content are protected separately, it would possible to enable pay-per-quality providing an additional degree of freedom to content delivery industry. Unfortunatelly, transcoding and protection entail huge doses of processing power at provider side and should be distributed. Moreover, processing key streams to decrypt enhancements that were encrypted separately can increase the complexity at receiver side. Cloud computing emerges as a potential solution for coping with large population of users with heterogeneous visualization devices. The elastic nature of cloud computing can be an advantage given the difficulty to predict the computing resources video content would require to be distributed during the entire content life. This article describes a system that distributes and parallelizes the video transcoding process as well as the content encryption, following the SaaS approach in cloud computing. Moreover, the article describes an experimental approach for generating and processing a flexible key stream that would help to simplify

关键词： transcoding Content protection keyword Cloud computing

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Homogenous HEVC video transcoding by transform coefficient removal

Homogenous HEVC video transcoding by transform coefficient r...

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International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Krzysztof Wegner Damian Karwowski Krzysztof Klimaszewski Jakub Stankowski Olgierd Stankiewicz Tomasz Grajek Chair of Multimedia Telecommunications and Microelectronics Poznan University of Technology Poznan

ISBN: (纸本)9781509063451

In this paper, a novel method of transcoding of HEVC encoded video is presented. The novel approach enables a very fast transcoding without the need for the image reconstruction. It is based on the principle of removing of the carefully selected coefficients from the bitstream. The removal of coefficients is done on the bitstream level and can easily be tailored to software as well as hardware implementations. The technique is able to provide a bitrate reduction in the order of up to 10%, with the image quality decrease of about 0.2-0.5dB.

关键词： transcoding Bit rate Image coding Streaming media Image reconstruction Transforms Software

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