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ACR360: A Dataset on Subjective 360° Video Quality Assessment Using ACR Methods
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-7550-5818
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0003-3604-2766
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-3283-2819
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-1730-9026
2023 (English)In: 2023 16th International Conference on Signal Processing and Communication System, ICSPCS 2023 - Proceedings / [ed] Wysocki B.J., Wysocki T.A., Institute of Electrical and Electronics Engineers (IEEE), 2023Conference paper, Published paper (Refereed)
Abstract [en]

The recent advances in immersive technologies have been essential in the development of a wide range of novel standalone and networked immersive media applications. The concepts of virtual reality, augmented reality, and mixed reality relate to different compositions of real and computer-generated virtual objects. In this context, 360° video streaming has become increasingly popular offering improved immersive experiences when viewed on a head-mounted display (HMD). An important component in the development of novel immersive media systems are subjective tests in which participants assess the quality of experience of representative test stimuli. In this paper, the annotated ACR360 dataset is presented which is publicly available on GitHub. The ACR360 dataset contains a wide range of psychophysical and psychophysiological data that was collected in Subjective tests on 360° video quality. The test stimuli were shown on an HMD and rated according to the absolute category rating (ACR) and modified ACR (MACR) methods. To support an easy exploration and utilization of the ACR360 dataset by the research community, its structure on GitHub is described and a comprehensive illustration of analysis options are provided for each data category. The ACR360 dataset may be used for conducting meta-analysis in combination with other datasets to improve precision and to pursue research questions that cannot be answered by an individual study. © 2023 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023.
Keywords [en]
360° video, absolute category rating, annotated dataset, Immersive media, quality assessment, Subjective test, Helmet mounted displays, Image quality, Mixed reality, Quality of service, Statistical tests, Subjective testing, Video streaming, Absolute category ratings, Annotated datasets, Head-mounted-displays, Immersive technologies, Media application, Video quality, Augmented reality
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:bth-25548DOI: 10.1109/ICSPCS58109.2023.10261151Scopus ID: 2-s2.0-85174510305ISBN: 9798350333510 (print)OAI: oai:DiVA.org:bth-25548DiVA, id: diva2:1810200
Conference
16th International Conference on Signal Processing and Communication System, ICSPCS 2023, Bydgoszcz, 6 Sept - 8 Sept 2023
Part of project
HINTS - Human-Centered Intelligent RealitiesVIATECH- Human-Centered Computing for Novel Visual and Interactive Applications, Knowledge Foundation
Funder
Knowledge Foundation, 20220068Knowledge Foundation, 20170056
Note

  

Available from: 2023-11-07 Created: 2023-11-07 Last updated: 2024-11-20Bibliographically approved
In thesis
1. Participants' Quality Experiences and Behavior in 360° Videos
Open this publication in new window or tab >>Participants' Quality Experiences and Behavior in 360° Videos
2025 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In the rapidly evolving virtual reality (VR) field, assessing video quality on head-mounted displays (HMDs) for 360° videos presents unique opportunities and challenges. As immersive multimedia becomes increasingly widespread, understanding how users perceive and evaluate the quality of 360° videos is essential. This thesis investigates the subjective quality assessment tests of 360° videos, examining how participants' VR experiences, viewing conditions, and exploration behaviors shape perceptions of quality. This thesis aims to perform subjective quality assessment tests to study and understand how participants perceive the quality of 360° videos on an HMD. The thesis starts with an extended summary of the field of subjective quality assessment for 360° videos, followed by eight key publications, and unfolds into three main parts.

The first part of the thesis focuses on data collection to establish ground truth. It includes a comprehensive survey of annotated 360° images and videos datasets related to subjective quality assessment. It also presents a set of datasets collected specifically for subjective quality assessment tests for 360° videos with different test methods and viewing conditions conducted as part of the research. The second part of the thesis investigates how varying levels of VR experience affect participants' video quality assessments. It compares two test methods, the absolute category rating (ACR) and the modified ACR (MACR) method, to evaluate 360° video quality. Furthermore, this part evaluates simulator sickness in participants viewing 360° video on an HMD and explores how their prior VR experience levels correlate with the occurrence of these symptoms. The third and final part of the thesis focuses on assessing viewing conditions and rating consistency. It involves conducting subjective quality assessment tests for 360° videos under different viewing conditions, such as standing and seated viewing, and providing a statistical analysis of the psychophysical and psychophysiological measures. This part also investigates the consistency of 360° video quality assessments through repeated subjective quality assessment tests under opportunity-limited conditions. It examines how quality assessments vary between the standing and seated viewing conditions and explores whether participants' subjective evaluations of 360° videos change over time or remain stable across repeated exposures.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2025. p. 255
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 2025:01
Keywords
360° Video, Immersive Multimedia, Video Quality Assessment, Participants' Experience, Head-Mounted Display, Virtual Reality, Subjective Tests, Standing Viewing, Seated Viewing
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:bth-27122 (URN)978-91-7295-493-9 (ISBN)
Public defence
2025-01-17, J1630, Campus Gräsvik, Karlskrona, 09:00 (English)
Opponent
Supervisors
Available from: 2024-11-21 Created: 2024-11-20 Last updated: 2024-11-28Bibliographically approved

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Elwardy, MajedZepernick, Hans-JuergenHu, YanChu, Thi My Chinh

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