Machine-Learning Based High Efficiency Rate Control for AV1

Yi Chen; Yunhao Mao; Shiqi Wang; Xianguo Zhang; Sam Kwong

doi:10.1109/MIPR54900.2022.00019

Machine-Learning Based High Efficiency Rate Control for AV1

Yi Chen^*, Yunhao Mao^*, Shiqi Wang^*, Xianguo Zhang, Sam Kwong^*

^*Corresponding author for this work

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

Recent years have witnessed the increasing demand of video coding technologies, which have been continuously developed to meet various requirements in video-related applications. Developed by Alliance for Open Media (AOM), the AOMedia Video 1 (AVl) is an open-source and royalty-free standard. Herein, we achieve high efficiency rate control for AVI based on the machine-learning model, which establishes the rate-quantization relationship in a data-driven manner. More specifically, the Supporting Vector Regression (SVR) is used for rate model parameter estimation. The model is trained using sufficient training data, and incorporated in the encoder. Compared to the default rate control scheme in AV 1, experimental results have shown that 2.01% bitrate could be saved with tolerable bitrate error.

Original language	English
Title of host publication	Proceedings - 5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022
Publisher	IEEE
Pages	65-70
ISBN (Electronic)	9781665495486
ISBN (Print)	978-1-6654-9549-3
DOIs	https://doi.org/10.1109/MIPR54900.2022.00019
Publication status	Published - 2022
Event	5th International Conference on Multimedia Information Processing and Retrieval (MIPR 2022) - Virtual, United States Duration: 2 Aug 2022 → 4 Aug 2022 http://www.ieee-mipr.org/history/2022/data/index.html

Publication series

Name	Proceedings - International Conference on Multimedia Information Processing and Retrieval, MIPR
ISSN (Print)	2770-4327
ISSN (Electronic)	2770-4319

Conference

Conference	5th International Conference on Multimedia Information Processing and Retrieval (MIPR 2022)
Place	United States
Period	2/08/22 → 4/08/22
Internet address	http://www.ieee-mipr.org/history/2022/data/index.html

Funding

This work was supported by the Hong Kong Innovation and Technology Commission (InnoHK Project CIMDA), Hong Kong RGC GRF Grant 9042816 (CityU 11209819) and Grant 9042958 (CityU 11203820), as well as the Tencent Rhino-Bird Fund.

Research Keywords

Quantization parameter (QP)
Rate control
Supporting vector regression
Video coding

RGC Funding Information

RGC-funded

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10.1109/MIPR54900.2022.00019

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Check CityUHK Library

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Cite this

Chen, Y., Mao, Y., Wang, S., Zhang, X., & Kwong, S. (2022). Machine-Learning Based High Efficiency Rate Control for AV1. In Proceedings - 5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022 (pp. 65-70). (Proceedings - International Conference on Multimedia Information Processing and Retrieval, MIPR). IEEE. https://doi.org/10.1109/MIPR54900.2022.00019

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title = "Machine-Learning Based High Efficiency Rate Control for AV1",

abstract = "Recent years have witnessed the increasing demand of video coding technologies, which have been continuously developed to meet various requirements in video-related applications. Developed by Alliance for Open Media (AOM), the AOMedia Video 1 (AVl) is an open-source and royalty-free standard. Herein, we achieve high efficiency rate control for AVI based on the machine-learning model, which establishes the rate-quantization relationship in a data-driven manner. More specifically, the Supporting Vector Regression (SVR) is used for rate model parameter estimation. The model is trained using sufficient training data, and incorporated in the encoder. Compared to the default rate control scheme in AV 1, experimental results have shown that 2.01% bitrate could be saved with tolerable bitrate error.",

keywords = "Quantization parameter (QP), Rate control, Supporting vector regression, Video coding",

author = "Yi Chen and Yunhao Mao and Shiqi Wang and Xianguo Zhang and Sam Kwong",

year = "2022",

doi = "10.1109/MIPR54900.2022.00019",

language = "English",

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booktitle = "Proceedings - 5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022",

address = "United States",

note = "5th International Conference on Multimedia Information Processing and Retrieval (MIPR 2022) ; Conference date: 02-08-2022 Through 04-08-2022",

url = "http://www.ieee-mipr.org/history/2022/data/index.html",

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Chen, Y , Mao, Y , Wang, S, Zhang, X & Kwong, S 2022, Machine-Learning Based High Efficiency Rate Control for AV1. in Proceedings - 5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022. Proceedings - International Conference on Multimedia Information Processing and Retrieval, MIPR, IEEE, pp. 65-70, 5th International Conference on Multimedia Information Processing and Retrieval (MIPR 2022), California, United States, 2/08/22. https://doi.org/10.1109/MIPR54900.2022.00019

Machine-Learning Based High Efficiency Rate Control for AV1. / Chen, Yi ; Mao, Yunhao ; Wang, Shiqi et al.
Proceedings - 5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022. IEEE, 2022. p. 65-70 (Proceedings - International Conference on Multimedia Information Processing and Retrieval, MIPR).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Machine-Learning Based High Efficiency Rate Control for AV1

AU - Chen, Yi

AU - Mao, Yunhao

AU - Wang, Shiqi

AU - Zhang, Xianguo

AU - Kwong, Sam

PY - 2022

Y1 - 2022

N2 - Recent years have witnessed the increasing demand of video coding technologies, which have been continuously developed to meet various requirements in video-related applications. Developed by Alliance for Open Media (AOM), the AOMedia Video 1 (AVl) is an open-source and royalty-free standard. Herein, we achieve high efficiency rate control for AVI based on the machine-learning model, which establishes the rate-quantization relationship in a data-driven manner. More specifically, the Supporting Vector Regression (SVR) is used for rate model parameter estimation. The model is trained using sufficient training data, and incorporated in the encoder. Compared to the default rate control scheme in AV 1, experimental results have shown that 2.01% bitrate could be saved with tolerable bitrate error.

AB - Recent years have witnessed the increasing demand of video coding technologies, which have been continuously developed to meet various requirements in video-related applications. Developed by Alliance for Open Media (AOM), the AOMedia Video 1 (AVl) is an open-source and royalty-free standard. Herein, we achieve high efficiency rate control for AVI based on the machine-learning model, which establishes the rate-quantization relationship in a data-driven manner. More specifically, the Supporting Vector Regression (SVR) is used for rate model parameter estimation. The model is trained using sufficient training data, and incorporated in the encoder. Compared to the default rate control scheme in AV 1, experimental results have shown that 2.01% bitrate could be saved with tolerable bitrate error.

KW - Quantization parameter (QP)

KW - Rate control

KW - Supporting vector regression

KW - Video coding

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U2 - 10.1109/MIPR54900.2022.00019

DO - 10.1109/MIPR54900.2022.00019

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-1-6654-9549-3

T3 - Proceedings - International Conference on Multimedia Information Processing and Retrieval, MIPR

SP - 65

EP - 70

BT - Proceedings - 5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022

PB - IEEE

T2 - 5th International Conference on Multimedia Information Processing and Retrieval (MIPR 2022)

Y2 - 2 August 2022 through 4 August 2022

ER -

Chen Y , Mao Y , Wang S, Zhang X, Kwong S. Machine-Learning Based High Efficiency Rate Control for AV1. In Proceedings - 5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022. IEEE. 2022. p. 65-70. (Proceedings - International Conference on Multimedia Information Processing and Retrieval, MIPR). Epub 2022 Sept 8. doi: 10.1109/MIPR54900.2022.00019

Machine-Learning Based High Efficiency Rate Control for AV1

Abstract

Publication series

Conference

Funding

Research Keywords

RGC Funding Information

Access Output

Other Access Options

Permanent Link

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GRF: Adaptive Dynamic Range Enhancement Oriented to High Dynamic Display

GRF: Intelligent Ultra High Definition Video Encoder Optimization for Future Versatile Video Coding

Cite this

Machine-Learning Based High Efficiency Rate Control for AV1

Abstract

Publication series

Conference

Funding

Research Keywords

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Projects

GRF: Adaptive Dynamic Range Enhancement Oriented to High Dynamic Display

GRF: Intelligent Ultra High Definition Video Encoder Optimization for Future Versatile Video Coding

Cite this