Machine-learning based VMAF prediction for HDR video content

被引：1

作者：

Mueller, Christoph ^{[1
]}

Steglich, Stephan ^{[1
]}

Gross, Sandra ^{[2
]}

Kremer, Paul ^{[2
]}

机构：

[1] Fraunhofer FOKUS, Berlin, Germany

[2] RTL Technol, Cologne, Germany

来源：

PROCEEDINGS OF THE 2023 PROCEEDINGS OF THE 14TH ACM MULTIMEDIA SYSTEMS CONFERENCE, MMSYS 2023 | 2023年

关键词：

VMAF; video quality; HDR; neural networks; machine learning;

D O I：

10.1145/3587819.3593941

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a methodology for predicting VMAF video quality scores for high dynamic range (HDR) video content using machine learning. To train the ML model, we are collecting a dataset of HDR and converted SDR video clips, as well as their corresponding objective video quality scores, specifically the Video Multimethod Assessment Fusion (VMAF) values. A 3D convolutional neural network (3D-CNN) model is being trained on the collected dataset. Finally, a hands-on demonstrator is developed to showcase the newly predicted HDR-VMAF metric in comparison to VMAF and other metric values for SDR content, and to conduct further validation with user testing.

引用

页码：328 / 332

页数：5

共 50 条

[1] Machine-Learning Based Prediction of Next HTTP Request Arrival Time in Adaptive Video Streaming
Pimpinella, Andrea
Redondi, Alessandro E. C.
Loh, Frank
Seufert, Michael
PROCEEDINGS OF THE 2021 17TH INTERNATIONAL CONFERENCE ON NETWORK AND SERVICE MANAGEMENT (CNSM 2021): SMART MANAGEMENT FOR FUTURE NETWORKS AND SERVICES, 2021, : 558 - 564
[2] Machine-Learning Based TCP Security Action Prediction
Zhao, Quanling
Sun, Jiawei
Ren, Hongjia
Sun, Guodong
2020 5TH INTERNATIONAL CONFERENCE ON MECHANICAL, CONTROL AND COMPUTER ENGINEERING (ICMCCE 2020), 2020, : 1325 - 1329
[3] Prediction of Nucleophilicity and Electrophilicity Based on a Machine-Learning Approach
Liu, Yidi
Yang, Qi
Cheng, Junjie
Zhang, Long
Luo, Sanzhong
Cheng, Jin-Pei
CHEMPHYSCHEM, 2023, 24 (14)
[4] HDR IMAGE QUALITY ASSESSMENT USING MACHINE-LEARNING BASED COMBINATION OF QUALITY METRICS
Choudhury, Anustup
Daly, Scott
2018 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2018), 2018, : 91 - 95
[5] Machine-Learning Aided Peer Prediction
Liu, Yang
Chen, Yiling
EC'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON ECONOMICS AND COMPUTATION, 2017, : 63 - 80
[6] Prediction of cholinergic compounds by machine-learning
Wijeyesakere S.J.
Wilson D.M.
Sue Marty M.
Wilson, Daniel M. (MWilson3@dow.com), 1600, Elsevier B.V. (13):
[7] Machine-learning based prediction of crash response of tubular structures
Sakaridis, Emmanouil
Karathanasopoulos, Nikolaos
Mohr, Dirk
INTERNATIONAL JOURNAL OF IMPACT ENGINEERING, 2022, 166
[8] Machine Learning Based Content-Agnostic Viewport Prediction for 360-Degree Video
Van Damme, Sam
Vega, Maria Torres
De Turck, Filip
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2022, 18 (02)
[9] A Development of Content-based Video Summarization System Using Machine-Learning and its Application to Analysis of Livestock Behavior
Zhi, Que
Saitoh, Tomoko
Nakajima, Mizuki
Saitoh, Tsuyoshi
INTERNATIONAL WORKSHOP ON ADVANCED IMAGE TECHNOLOGY (IWAIT) 2019, 2019, 11049
[10] Machine-Learning Based Prediction Model for Prognosis of IgA Nephropathy Patients
Park, Sehoon
Koh, Eun Sil
Baek, Chung Hee
Kim, Yong Chul
Lee, Jung Pyo
Kim, Dong Ki
Han, Seung Hyeok
Chin, Ho Jun
Joo, Kwon Wook
Kim, Yon Su
Lee, Hajeong
JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY, 2022, 33 (11): : 800 - 801

← 1 2 3 4 5 →