VQEG Column: VQEG Meeting Dec. 2020 (virtual/online)

VQEG website: www.vqeg.org
Jesús Gutiérrez (jesus.gutierrez@upm.es), Universidad Politécnica de Madrid (Spain)
Kjell Brunnström (kjell.brunnstrom@ri.se), RISE (Sweden) 


Welcome to the third column on the ACM SIGMM Records from the Video Quality Experts Group (VQEG).
The last VQEG plenary meeting took place online from 14 to 18 December. Given the current circumstances, it was organized all online for the second time, with multiple sessions distributed over five to six hours each day allowing remote participation of people from different time zones. About 130 participants from 24 different countries registered to the meeting and could attend the several presentations and discussions that took place in all working groups.
This column provides an overview of this meeting, while all the information, minutes, files (including the presented slides), and video recordings from the meeting are available online in the VQEG meeting website. As highlights of interest for the SIGMM community, apart from several interesting presentations of state-of-the-art works, relevant contributions to ITU recommendations related to multimedia quality assessment were reported from various groups (e.g., on adaptive bitrate streaming services, on subjective quality assessment of 360-degree videos, on statistical analysis of quality assessments, on gaming applications, etc.), the new group on quality assessment for health applications was launched, and an interesting session on 5G use cases took place, as well as a workshop dedicated to user testing during Covid-19. In addition, new efforts have been launched related to the research on quality metrics for live media streaming applications, and to provide guidelines on implementing objective video quality metrics (ahead of PSNR) to the video compression community.
We encourage those readers interested in any of the activities going on in the working groups to check their websites and subscribe to the corresponding reflectors, to follow them and get involved.

Overview of VQEG Projects

Audiovisual HD (AVHD)

AVHD/P.NATS2 project was a joint collaboration between VQEG and ITU SG12, whose goal was to develop a multitude of objective models, varying in terms of complexity/type of input/use-cases for the assessment of video quality in adaptive bitrate streaming services over reliable transport up to 4K. The report of this project, which finished in January 2020, was approved in this meeting. In summary, it resulted in 10 model categories with models trained and validated on 26 subjective datasets. This activity resulted in 4 ITU standards (ITU-T Rec. P.1204 in [1], P.1204.3 in [2], P.1204.4 in [3], P.1204.5 in [4], a dataset created during this effort and a journal publication reporting details on the validation tests [5]. In this sense, one presentation by Alexander Raake (TU Ilmenau) provided details on the P.NATS Phase 2 project and the resulting ITU recommendations, while details of the processing chain used in the project were presented by Werner Robitza (AVEQ GmbH) and David Lindero (Ericsson).
In addition to this activity, there were various presentations covering topics related to this group. For instance, Cindy Chen, Deepa Palamadai Sundar, and Visala Vaduganathan (Facebook) presented their work on hardware acceleration of video quality metrics. Also from Facebook, Haixiong Wang presented their work on efficient measurement of quality at scale in their video ecosystem [6]. Lucjan Janowski (AGH University) proposed a discussion on more ecologically valid subjective experiments, Alan Bovik (University of Texas at Austin) presented a hitchhiker’s guide to SSIM, and Ali Ak (Université de Nantes) presented a comprehensive analysis of crowdsourcing for subjective evaluation of tone mapping operators. Finally, Rohit Puri (Twitch) opened a discussion on the research on QoE metrics for live media streaming applications, which led to the agreement to start a new sub-project within AVHD group on this topic.

Psycho-Physiological Quality Assessment (PsyPhyQA)

The chairs of the PsyPhyQA group provided an update on the activities carried out. In this sense, a test plan for psychophysiological video quality assessment was established and currently the group is aiming to develop ideas to do quality assessment tests with psychophysiological measures in times of a pandemic and to collect and discuss ideas about possible joint works. In addition, the project is trying to learn about physiological correlates of simulator sickness, and in this sense, a presentation was delivered J.P. Tauscher (Technische Universität Braunschweig) on exploring neural and peripheral physiological correlates of simulator sickness. Finally, Waqas Ellahi (Université de Nantes) gave a presentation on visual fidelity of tone mapping operators from gaze data using HMM [7].

Quality Assessment for Health applications (QAH)

This was the first meeting for this new QAH group. The chairs informed about the first audio call that took place on November to launch the project, know how many people are interested in this project, what each member has already done on medical images, what each member wants to do in this joint project, etc.
The plenary meeting served to collect ideas about possible joint works and to share experiences on related studies. In this sense, Lucie Lévêque (Université Gustave Eiffel) presented a review on subjective assessment of the perceived quality of medical images and videos, Maria Martini (Kingston University London) talked about the suitability of VMAF for quality assessment of medical videos (ultrasound & wireless capsule endoscopy), and Jorge Caviedes (ASU) delivered a presentation on cognition inspired diagnostic image quality models.

Statistical Analysis Methods (SAM)

The update report from SAM group presented the ongoing progress on new methods for data analysis, including the discussion with ITU-T (P.913 [8]) and ITU-R (BT.500 [9]) about including a new one in the recommendations.
Several interesting presentations related to the ongoing work within SAM were delivered. For instance, Jakub Nawala (AGH University) presented the “su-JSON”, a uniform JSON-based subjective data format, as well as his work on describing subjective experiment consistency by p-value p–p plots. An interesting discussion was raised by Lucjan Janowski (AGH University) on how to define the quality of a single sequence, analyzing different perspectives (e.g., crowd, experts, psychology, etc.). Also, Babak Naderi (TU Berlin) presented an analysis on the relation on Mean Opinion Score (MOS) and ranked-based statistics. Recent advances on Netflix quality metric VMAF were presented by Zhi Li (Netflix), especially on the properties of VMAF in the presence of image enhancement. Finally, two more presentations addressed the progress on statistical analyses of quality assessment data, one by Margaret Pinson (NTIA/ITS) on the computation of confidence intervals, and one by Suiyi Ling (Université de Nantes) on a probabilistic model to recover the ground truth and annotator’s behavior.

Computer Generated Imagery (CGI)

The report from the chairs of the CGI group covered the progress on the research on assessment methodologies for quality assessment of gaming services (e.g., ITU-T P.809 [10]), on crowdsourcing quality assessment for gaming application (P.808 [11]), on quality prediction and opinion models for cloud gaming (e.g., ITU-T G.1072 [12]), and on models (signal-, bitstream-, and parametric-based models) for video quality assessment of CGI content (e.g., nofu, NDNetGaming, GamingPara, DEMI, NR-GVQM, etc.).
In terms of planned activities, the group is targeting the generation of new gaming datasets and tools for metrics to assess gaming QoE, but also the group is aiming at identifying other topics of interest in CGI rather than gaming content.
In addition, there was a presentation on updates on gaming standardization activities and deep learning models for gaming quality prediction by Saman Zadtootaghaj (TU Berlin), another one on subjective assessment of multi-dimensional aesthetic assessment for mobile game images by Suiyi Ling (Université de Nantes), and one addressing quality assessment of gaming videos compressed via AV1 by Maria Martini (Kingston University London), leading to interesting discussions on those topics.

No Reference Metrics (NORM)

The session for NORM group included a presentation on the differences among existing implementations of spatial and temporal perceptual information indices (SI and TI as defined in ITU-T P.910 [13]) by Cosmin Stejerean (Facebook), which led to an open discussion and to the agreement on launching an effort to clarify the ambiguous details that have led to different implementations (and different results), to generate test vectors for reference and validation of the implementations and to address the computation of these indicators for HDR content. In addition, Margaret Pinson (NTIA/ITS) presented the paradigm of no-reference metric research analyzing design problems and presenting a framework for collaborative development of no-reference metrics for image and video quality. Finally, Ioannis Katsavounidis (Facebook) delivered a talk on addressing the addition of video quality metadata in compressed bitstreams. Further discussions on these topics are planned in the next month within the group.

Joint Effort Group (JEG) – Hybrid

The JEG-Hybrid group is currently working in collaboration with Sky Group in determining when video quality metrics are likely to inaccurately predict the MOS and on modelling single observers’ quality perception based in artificial intelligence techniques. In this sense, Lohic Fotio (Politecnico di Tornio) presented his work on artificial intelligence-based observers for media quality assessment. Also, together with Florence Agboma (Sky UK) they presented their work on comparing commercial and open source video quality metrics for HD constant bitrate videos. Finally, Dariusz Grabowski (AGH University) presented his work on comparing full-reference video quality metrics using cluster analysis.

Quality Assessment for Computer Vision Applications (QACoViA)

The QACoViA group announced Lu Zhang (INSA Rennes) as new third co-chair, who will also work in the near future in a project related to image compression for optimized recognition by distributed neural networks. In addition, Mikołaj Leszczuk (AGH University) presented a report on a recently finished project related to objective video quality assessment method for recognition tasks, in collaboration with Huawei through its Innovation Research Programme.

5G Key Performance Indicators (5GKPI)

The 5GKPI session was oriented to identify possible interested partners and joint works (e.g., contribution to ITU-T SG12 recommendation G.QoE-5G [14], generation of open/reference datasets, etc.). In this sense, it included four presentations of use cases of interest: tele-operated driving by Yungpeng Zang (5G Automotive Association), content production related to the European project 5G-Records by Paola Sunna (EBU), Augmented/Virtual Reality by Bill Krogfoss (Bell Labs Consulting), and QoE for remote controlled use cases by Kjell Brunnström (RISE).

Immersive Media Group (IMG)

A report on the updates within the IMG group was initially presented, especially covering the current joint work investigating the subjective quality assessment of 360-degree video. In particular, a cross-lab test, involving 10 different labs, were carried out at the beginning of 2020 resulting in relevant outcomes including various contributions to ITU SG12/Q13 and MPEG AhG on Quality of Immersive Media. It is worth noting that the new ITU-T recommendation P.919 [15], related to subjective quality assessment of 360-degree videos (in line with ITU-R BT.500 [8] or ITU-T P.910 [13]), was approved in mid-October, and was supported by the results of these cross-lab tests. 
Furthermore, since these tests have already finished, there was a presentation by Pablo Pérez (Nokia Bell-Labs) on possible future joint activities within IMG, which led to an open discussion after it that will continue in future audio calls.
In addition, a total of four talks covered topics related to immersive media technologies, including an update from the Audiovisual Technology Group of the TU Ilmenau on immersive media topics, and a presentation of a no-reference quality metric for light field content based on a structural representation of the epipolar plane image by Ali Ak and Patrick Le Callet (Université de Nantes) [16]. Also, there were two presentations related to 3D graphical contents, one addressing the perceptual characterization of 3D graphical contents based on visual attention patterns by Mona Abid (Université de Nantes), and another one comparing subjective methods for quality assessment of 3D graphics in virtual reality by Yana Nehmé (INSA Lyon). 

Intersector Rapporteur Group on Audiovisual Quality Assessment (IRG-AVQA) and Q19 Interim Meeting

Chulhee Lee (Yonsei University) chaired the IRG-AVQA session, providing an overview on the progress and recent works within ITU-R WP6C in HDR related topics and ITU-T SG12 Questions 9, 13, 14, 19 (e.g., P.NATS Phase 2 and follow-ups, subjective assessment of 360-degree video, QoE factors for AR applications, etc.). In addition, a new work item was announced within ITU-T SG9: End-to-end network characteristics requirements for video services (J.pcnp-char [17]).
From the discussions raised during this session, a new dedicated group was set up to work on introducing and provide guidelines on implementing objective video quality metrics, ahead of PSNR, to the video compression community. The group was named “Implementers Guide for Video Quality Metrics (IGVQM)” and will be chaired by Ioannis Katsavounidis (Facebook), accounting with the involvement of several people from VQEG.
After the IRG-AVQA session, the Q19 interim meeting took place with a report by Chulhee Lee and a presentation by Zhi Li (Netflix) on an update on improvements on subjective experiment data analysis process.

Other updates

Apart from the aforementioned groups, the Human Factors for Visual Experience (HVEI) is still active coordinating VQEG activities in liaison with the IEEE Standards Association Working Groups on HFVE, especially on perceptual quality assessment of 3D, UHD and HD contents, quality of experience assessment for VR and MR, quality assessment of light-field imaging contents, and deep-learning-based assessment of visual experience based on human factors. In this sense, there are ongoing contributions from VQEG members to IEEE Standards.
In addition, there was a workshop dedicated to user testing during Covid-19, which included a presentation on precaution for lab experiments by Kjell Brunnström (RISE), another presentation by Babak Naderi (TU Berlin) on subjective tests during the pandemic, and a break-out session for discussions on the topic.

Finally, the next VQEG plenary meeting will take place in spring 2021 (exact dates still to be agreed), probably online again.


[1] ITU-T Rec. P.1204. Video quality assessment of streaming services over reliable transport for resolutions up to 4K, 2020.
[2] ITU-T Rec. P.1204.3. Video quality assessment of streaming services over reliable transport for resolutions up to 4K with access to full bitstream information, 2020.
[3] ITU-T Rec. P.1204.4. Video quality assessment of streaming services over reliable transport for resolutions up to 4K with access to full and reduced reference pixel information, 2020.
[4] ITU-T Rec. P.1204.5. Video quality assessment of streaming services over reliable transport for resolutions up to 4K with access to transport and received pixel information, 2020.
[5] A. Raake, S. Borer, S. Satti, J. Gustafsson, R.R.R. Rao, S. Medagli, P. List, S. Göring, D. Lindero, W. Robitza, G. Heikkilä, S. Broom, C. Schmidmer, B. Feiten, U. Wüstenhagen, T. Wittmann, M. Obermann, R. Bitto, “Multi-model standard for bitstream-, pixel-based and hybrid video quality assessment of UHD/4K: ITU-T P.1204”, IEEE Access, vol. 8, pp. 193020-193049, Oct. 2020.
[6] S.L. Regunathan, H. Wang, Y. Zhang, Y. R. Liu, D. Wolstencroft, S. Reddy, C. Stejerean, S. Gandhi, M. Chen, P. Sethi, A, Puntambekar, M. Coward, I. Katsavounidis, “Efficient measurement of quality at scale in Facebook video ecosystem”, in Applications of Digital Image Processing XLIII, vol. 11510, p. 115100J, Aug. 2020.
[7] W. Ellahi, T. Vigier and P. Le Callet, “HMM-Based Framework to Measure the Visual Fidelity of Tone Mapping Operators”, IEEE International Conference on Multimedia & Expo Workshops (ICMEW), London, United Kingdom, Jul. 2020.
[8] ITU-R Rec. BT.500-14. Methodology for the subjective assessment of the quality of television pictures, 2019.
[9] ITU-T Rec. P.913. Methods for the subjective assessment of video quality, audio quality and audiovisual quality of Internet video and distribution, 2016.
[10] ITU-T Rec. P.809. Subjective evaluation methods for gaming quality, 2018.
[11] ITU-T Rec. P.808. Subjective evaluation of speech quality with a crowdsourcing approach, 2018.
[12] ITU-T Rec. G.1072. Opinion model predicting gaming quality of experience for cloud gaming services, 2020.
[13] ITU-T Rec. P.910. Subjective video quality assessment methods for multimedia applications, 2008.
[14] ITU-T Rec. G.QoE-5G. QoE factors for new services in 5G networks, 2020 (under study).
[15] ITU-T Rec. P.919. Subjective test methodologies for 360º video on head-mounted displays, 2020.
[16] A. Ak, S. Ling and P. Le Callet, “No-Reference Quality Evaluation of Light Field Content Based on Structural Representation of The Epipolar Plane Image”, IEEE International Conference on Multimedia & Expo Workshops (ICMEW), London, United Kingdom, Jul. 2020.
[17] ITU-T Rec. J.pcnp-char. E2E Network Characteristics Requirement for Video Services, 2020 (under study).

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