Category Archives: Feature

Introduction

The University of Klagenfurt (Austria) hosted from July 01-05, 2024 a plenary meeting of the Video Quality Experts Group (VQEG). More than 110 participants from 20 different countries could attend this meeting in person and remotely.

The first three days of the meeting were dedicated to presentations and discussions about topics related to the ongoing projects within VQEG, while during the last two days an IUT-T Study Group G12 Question 19 (SG12/Q9) interim meeting took place. All the related information, minutes, and files from the meeting are available online in the VQEG meeting website, and video recordings of the meeting are available in Youtube.

All the topics mentioned bellow can be of interest for the SIGMM community working on quality assessment, but special attention can be devoted to the workshop on quality assessment towards 6G held within the 5GKPI group, and to the dedicated meeting of the IMG group hosted by the Distributed and Interactive Systems Group (DIS) of the CWI in September 2024 to work on ITU-T P.IXC recommendation. In addition, during those days there was a co-located ITU-T SG12 Q19 interim meeting.

Readers of these columns interested in the ongoing projects of VQEG are encouraged to subscribe to their corresponding reflectors to follow the activities going on and to get involved in them.

Another plenary meeting of VQEG has taken place from 18th 22nd of November 2024 and will be reported in a following issue of the ACM SIGMM Records.

Overview of VQEG Projects

Audiovisual HD (AVHD)

The AVHD group works on developing and validating subjective and objective methods to analyze commonly available video systems. During the meeting, there were 8 presentations covering very diverse topics within this project, such as open-source efforts, quality models, and subjective assessment methodologies:

• Jonas Birmé (Eyevinn Technology, Sweden) presented their work on lowering the barrier for using open source and contributing to a sustainable business. In this sense, he presented Open Source Cloud that offers open source as a service, removing the need for users of to maintain their own infrastructure in applications such as video encoding and quality assurance.
• Hadi Amirpour (University of Klagenfurt, Austria) and Jingwen Zhu (Nantes Université, France) presented their joint work that explored the use of Just Noticeable Differences (JND) to select bitratere-solution pairs for constructing a bitrate ladder with respect to the proportion of Satisfied User Ratio (SUR).
• Rafał Mantiuk (University of Cambridge, UK) talked about a family of metrics that directly model low-level human vision by incorporating the models of contrast sensitivity, contrast masking, and colour vision, which can bring many advantages, such as explainability, robustness to unseen distortion, etc. Those metrics include HDR-VDP-3, Foveated Video VDP, and Colour Video VDP, all publicly available as open-source projects.
• Dounia Hammou (University of Cambridge, UK) presented a study on the effect of viewing distance and display luminance on the visibility of HDR video streaming distortions, including a new video quality dataset, HDR-VDC, which captures the quality degradation of HDR content due to AV1 coding artifacts and the resolution reduction.
• Tomasz Konaszynski (AGH University of Krakow, Poland) talked about the impact of the structure and order of the stimuli presented to the viewers during subjective quality tests.
• Dominik Keller (Technische Universität Ilmenau, Germany) an open 8K HDR source dataset for video quality research (AVT-VQDB-UHD-2-HDR).
• Syed Uddin (AGH University of Krakow, Poland) presented his analysis on how effectively low-latency algorithms in DASH.JS enhance the user experience.
• Avrajyoti Dutta (AGH University of Krakow, Poland) presented a study that investigates the evaluation of subjective video quality utilizing short video clips on a crowd-sourcing platform.

Quality Assessment for Health applications (QAH)

The QAH group is focused on the quality assessment of health applications. It addresses subjective evaluation, generation of datasets, development of objective metrics, and task-based approaches. Joshua Maraval and Meriem Outtas (INSA Rennes, France) a dual rig approach for capturing multi-view video and spatialized audio capture for medical training applications, including a dataset for quality assessment purposes.

Statistical Analysis Methods (SAM)

The group SAM investigates on analysis methods both for the results of subjective experiments and for objective quality models and metrics. The following presentations were delivered during the meeting:  

• Rafał Mantiuk (University of Cambridge, UK) presented lessons learned, covering the main strengths and caveats, from a large experience performing pairwise comparison experiments, which includes the publication of datasets, software tools, and methods.
• Mohsen Jenadeleh (University of Konstanz, Germany) presented an experiment and an annotated dataset on image quality evaluation with triplet comparisons, in the particular case of multi-dimensional scaling. Also, he presented a study on the effects of immediate feedback on crowdworkers’ performance in subjective image quality assessment tasks using paired comparisons.
• Simon H. Del Pin (Norwegian University of Science and Technology, Norway) and Dietmar Saupe (University of Konstanz, Germany) presented their study on national differences in image quality assessment using discrete rating based on 3 large-scale datasets.
• Andréas Pastor (Nantes Université, France) proposed a new framework for perceptually-optimized encoding using the “libaom” of the AV1 codec, which aims to improve perceptual quality and compression efficiency.
• Hadi Amirpour (University of Klagenfurt, Austria) and Jingwen Zhu (Nantes Université, France) presented their joint work on analyzing the uncertainty of Satisfied User Ratios (SUR) and studying how different video quality metrics perform to estimate SUR.

No Reference Metrics (NORM)

The group NORM addresses a collaborative effort to develop no-reference metrics for monitoring visual service quality. In this sense, the following topics were covered:

• Yixu Chen (Amazon, US) presented their development of a metric tailored for video compression and scaling, which can extrapolate to different dynamic ranges, is suitable for real-time video quality metrics delivery in the bitstream, and can achieve better correlation than VMAF and P.1204.3.
• Filip Korus (AGH University of Krakow, Poland) talked about the detection of hard-to-compress video sequences (e.g., video content generated during e-sports events) based on objective quality metrics, and proposed a machine-learning model to assess compression difficulty.
• Hadi Amirpour (University of Klagenfurt, Austria) provided a summary of activities in video complexity analysis, covering from VCA to DeepVCA and describing a Grand Challenge on Video Complexity.
• Pierre Lebreton (Capacités & Nantes Université, France) presented a new dataset that allows studying the differences among existing UGC video datasets, in terms of characteristics, covered range of quality, and the implication of these quality ranges on training and validation performance of quality prediction models.
• Zhengzhong Tu (Texas A&M University, US) introduced a comprehensive video quality evaluator (COVER) designed to evaluate video quality holistically, from a technical, aesthetic, and semantic perspective. It is based on leveraging three parallel branches: a Swin Transformer backbone to predict technical quality, a ConvNet employed to derive aesthetic quality, and a CLIP image encoder to obtain semantic quality.

Emerging Technologies Group (ETG)

The ETG group focuses on various aspects of multimedia that, although they are not necessarily directly related to “video quality”, can indirectly impact the work carried out within VQEG and are not addressed by any of the existing VQEG groups. In particular, this group aims to provide a common platform for people to gather together and discuss new emerging topics, possible collaborations in the form of joint survey papers, funding proposals, etc. During this meeting, the following presentations were delivered:

• Abhijay Ghildyal (Portland State University, Canada) talked about the current status, gaps, shortcomings, and opportunities that the new paradigms of AI-generated image and video content brings.
• Kjell Brunnström (RISE, Sweden) presented his work on augmented reality head-up displays and digital rear view mirrors in cars, analyzing different factors, such as height of cameras, size of the field of view, etc.
• Mohammad Ghasempour (University of Klagenfurt, Austria) presented their approach for energy-aware video streaming, based on the appropriate selection of spatial and temporal resolution of videos.
• Mathias Wien (RWTH Aachen University, Germany) provided the updates on testing activities on video quality assessment within MPEG, including the creation of the CVQM database (Coded Video for study of Quality Metrics) covering both conventional and neural network-based video coding schemes.
• Henrique Souza Rossi (Luleå University of Technology, Sweden) presented his study on subjective QoE assessment for VR cloud-based gaming, focused on a first-person shooter game.

Joint Effort Group (JEG) – Hybrid

The group JEG-Hybrid addresses several areas of Video Quality Assessment (VQA), such as the creation of a large dataset for training such models using full-reference metrics instead of subjective metrics. In addition, the group includes the VQEG project Implementer’s Guide for Video Quality Metrics (IGVQM). The chair of this group,  Enrico Masala (Politecnico di Torino, Italy) presented the updates on the latest activities going on, including the status of the IGVQM project and a new image dataset, which will be partially subjectively annotated, to train DNN models to predict single user’s subjective quality perception. In addition to this:

• Lohic Fotio Tiotsop (Politecnico di Torino, Italy) presented various advances on modeling subject scoring behaviors, such as a new approach to estimate the subjective quality from noisy subjective ratings and a novel subject scoring model that allows to highlight several peculiar. He also presented the development of a DNN-based model to predict individual subjective quality of images with multiple distortions, which included the creation of a dataset comprising two million samples with synthetic labels derived from human annotation.
• Maria Martini (Kingston University London, UK) followed up from a presentation delivered in a previous VQEG meeting, highlighting the relationship between PSNR and SSIM for DCT-based compressed images and video, including comparisons with other approximations of the relationships between the two.

Immersive Media Group (IMG)

The IMG group researches on the quality assessment of immersive media technologies. Currently, the main joint activity of the group is the development of a test plan to evaluate the QoE of immersive interactive communication systems, which is carried out in collaboration with ITU-T through the work item P.IXC. In this meeting, Pablo Pérez (Nokia XR Lab, Spain) and Jesús Gutiérrez (Universidad Politécnica de Madrid, Spain) provided an update on the progress of the test plan, reviewing the status of the subjective tests that were being performed at the 13 involved labs. Also in relation with this test plan:

• Jesús Gutiérrez and Miguel Die (Universidad Politécnica de Madrid, Spain) presented preliminary results from the subjective tests carried out to study the impact on remote communication of display technology with the real-time FVV Live system.
• Felix Immohr (Technische Universität Ilmenau, Germany) presented the results of a study to assess the effect of spatial audio on audiovisual plausibility and presence perception in a three-user interactive communication scenario.

In relation with other topics addressed by IMG:

•  Kamran Javidi and Maria Martini (Kingston University London, UK) presented two light field datasets: 1) a display-specific turntable-based dataset for subjective quality assessment (KULF-TT53), and 2) a video dataset of scenes with moving objects captured with a plenoptic video camera.
• Stephan Fremerey (Technische Universität Ilmenau, Germany) presented an open-source dataset to evaluate cognitive performance including source audiovisual 360° video and immersive CGI multi-talker content.

In addition, a specific meeting of the group was held at Distributed and Interactive Systems Group (DIS) of CWI in Amsterdam (Netherlands) from the 2nd to the 4th of September to progress on the joint test plan for evaluating immersive communication systems. A total of 26 international experts from seven countries (Netherlands, Spain, Italy, UK, Sweden, Germany, US, and Poland) participated, with 7 attending online. In particular, the meeting featured presentations on the status of tests run by 13 participating labs, leading to insightful discussions and progress towards the ITU-T P.IXC recommendation.

Quality Assessment for Computer Vision Applications (QACoViA)

The group QACoViA addresses the study the visual quality requirements for computer vision methods, where the final user is an algorithm. In this meeting, Mikołaj Leszczuk (AGH University of Krakow, Poland) presented a study introducing a novel evaluation framework designed to address accurately predicting the impact of different quality factors on recognition algorithm, by focusing on machine vision rather than human perceptual quality metrics.

5G Key Performance Indicators (5GKPI)

The 5GKPI group studies relationship between key performance indicators of new 5G networks and QoE of video services on top of them. In this meeting, a workshop was organized by Pablo Pérez (Nokia XR Lab, Spain) and Kjell Brunnström (RISE, Sweden) on “Future directions of 5GKPI: Towards 6G“.

The workshop consisted of a set of diverse topics such as: QoS and QoE management in 5G/6G networks by (Michelle Zorzi, University of Padova, Italy); parametric QoE models and QoE management by Tobias Hoßfeld (University of. Würzburb, Germany) and Pablo Pérez (Nokia XR Lab, Spain); current status of standardization and industry by Kjell Brunnström (RISE, Sweden) and Gunilla Berndtsson (Ericsson); content and applications provider perspectives on QoE management by François Blouin (Meta, US); and communications service provider perspectives by Theo Karagioules and Emir Halepovic (AT&T, US). In addition, a panel moderated by Narciso García (Universidad Politécnica de Madrid, Spain) with Christian Timmerer (University of Klagenfurt, Austria), Enrico Masala (Politecnico di Torino, Italy) and Francois Blouin (Meta, US) as speakers.

Human Factors for Visual Experiences (HFVE)

The HFVE group covers human factors related to audiovisual experiences and upholds the liaison relation between VQEG and the IEEE standardization group P3333.1. In this meeting, there were two presentations related to these topics:

• Mikołaj Leszczuk and Kamil Koniuch (AGH University of Krakow, Poland) presented a two-part insight into the realm of image quality assessment: 1) it provided an overview of the TUFIQoE project (Towards Better Understanding of Factors Influencing the QoE by More Ecologically-Valid Evaluation Standards) with a focus on challenges related to ecological validity; and 2) it delved into the ‘Psychological Image Quality’ experiment, highlighting the influence of emotional content on multimedia quality perception.

• Ali Ak (Capacités & Nantes Université, France) presented a video quality dataset with Iphone HDR videos and AV1 encoding (Nantes-MobileHDRVQA) and a study on the potential use of crowdsourcing platforms for acceptability and annoyance experiments.

The 148th MPEG meeting took place in Kemer, Türkiye, from November 4 to 8, 2024. The official press release can be found here and includes the following highlights:

• Point Cloud Coding: AI-based point cloud coding & enhanced G-PCC
• MPEG Systems: New Part of MPEG DASH for redundant encoding and packaging, reference software and conformance of ISOBMFF, and a new structural CMAF brand profile
• Video Coding: New part of MPEG-AI and 2nd edition of conformance and reference software for MPEG Immersive Video (MIV)
• MPEG completes subjective quality testing for film grain synthesis using the Film Grain Characteristics SEI message

Point Cloud Coding

At the 148^th MPEG meeting, MPEG Coding of 3D Graphics and Haptics (WG 7) launched a new AI-based Point Cloud Coding standardization project. MPEG WG 7 reviewed six responses to a Call for Proposals (CfP) issued in April 2024 targeting the full range of point cloud formats, from dense point clouds used in immersive applications to sparse point clouds generated by Light Detection and Ranging (LiDAR) sensors in autonomous driving. With bit depths ranging from 10 to 18 bits, the CfP called for solutions that could meet the precision requirements of these varied use cases.

Among the six reviewed proposals, the leading proposal distinguished itself with a hybrid coding strategy that integrates end-to-end learning-based geometry coding and traditional attribute coding. This proposal demonstrated exceptional adaptability, capable of efficiently encoding both dense point clouds for immersive experiences and sparse point clouds from LiDAR sensors. With its unified design, the system supports inter-prediction coding using a shared model with intra-coding, applicable across various bitrate requirements without retraining. Furthermore, the proposal offers flexible configurations for both lossy and lossless geometry coding.

Performance assessments highlighted the leading proposal’s effectiveness, with significant bitrate reductions compared to traditional codecs: a 47% reduction for dense, dynamic sequences in immersive applications and a 35% reduction for sparse dynamic sequences in LiDAR data. For combined geometry and attribute coding, it achieved a 40% bitrate reduction across both dense and sparse dynamic sequences, while subjective evaluations confirmed its superior visual quality over baseline codecs.

The leading proposal has been selected as the initial test model, which can be seen as a baseline implementation for future improvements and developments. Additionally, MPEG issued a working draft and common test conditions.

Research aspects: The initial test model, like those for other codec test models, is typically available as open source. This enables both academia and industry to contribute to refining various elements of the upcoming AI-based Point Cloud Coding standard. Of particular interest is how training data and processes are incorporated into the standardization project and their impact on the final standard.

Another point cloud-related project is called Enhanced G-PCC, which introduces several advanced features to improve the compression and transmission of 3D point clouds. Notable enhancements include inter-frame coding, refined octree coding techniques, Trisoup surface coding for smoother geometry representation, and dynamic Optimal Binarization with Update On-the-fly (OBUF) modules. These updates provide higher compression efficiency while managing computational complexity and memory usage, making them particularly advantageous for real-time processing and high visual fidelity applications, such as LiDAR data for autonomous driving and dense point clouds for immersive media.

By adding this new part to MPEG-I, MPEG addresses the industry’s growing demand for scalable, versatile 3D compression technology capable of handling both dense and sparse point clouds. Enhanced G-PCC provides a robust framework that meets the diverse needs of both current and emerging applications in 3D graphics and multimedia, solidifying its role as a vital component of modern multimedia systems.

MPEG Systems Updates

At its 148^th meeting, MPEG Systems (WG 3) worked on the following aspects, among others:

• New Part of MPEG DASH for redundant encoding and packaging
• Reference software and conformance of ISOBMFF
• A new structural CMAF brand profile

The second edition of ISO/IEC 14496-32 (ISOBMFF) introduces updated reference software and conformance guidelines, and the new CMAF brand profile supports Multi-View High Efficiency Video Coding (MV-HEVC), which is compatible with devices like Apple Vision Pro and Meta Quest 3.

The new part of MPEG DASH, ISO/IEC 23009-9, addresses redundant encoding and packaging for segmented live media (REAP). The standard is designed for scenarios where redundant encoding and packaging are essential, such as 24/7 live media production and distribution in cloud-based workflows. It specifies formats for interchangeable live media ingest and stream announcements, as well as formats for generating interchangeable media presentation descriptions. Additionally, it provides failover support and mechanisms for reintegrating distributed components in the workflow, whether they involve file-based content, live inputs, or a combination of both.

Research aspects: With the FDIS of MPEG DASH REAP available, the following topics offer potential for both academic and industry-driven research aligned with the standard’s objectives (in no particular order or priority):

• Optimization of redundant encoding and packaging: Investigate methods to minimize resource usage (e.g., computational power, storage, and bandwidth) in redundant encoding and packaging workflows. Explore trade-offs between redundancy levels and quality of service (QoS) in segmented live media scenarios.
• Interoperability of live media Ingest formats: Evaluate the interoperability of the standard’s formats with existing live media workflows and tools. Develop techniques for seamless integration with legacy systems and emerging cloud-based media workflows.
• Failover mechanisms for cloud-based workflows: Study the reliability and latency of failover mechanisms in distributed live media workflows. Propose enhancements to the reintegration of failed components to maintain uninterrupted service.
• Standardized stream announcements and descriptions: Analyze the efficiency and scalability of stream announcement formats in large-scale live streaming scenarios. Research methods for dynamically updating media presentation descriptions during live events.
• Hybrid workflow support: Investigate the challenges and opportunities in combining file-based and live input workflows within the standard. Explore strategies for adaptive workflow transitions between live and on-demand content.
• Cloud-based workflow scalability: Examine the scalability of the REAP standard in high-demand scenarios, such as global live event streaming. Study the impact of cloud-based distributed workflows on latency and synchronization.
• Security and resilience: Research security challenges related to redundant encoding and packaging in cloud environments. Develop techniques to enhance the resilience of workflows against cyberattacks or system failures.
• Performance metrics and quality assessment: Define performance metrics for evaluating the effectiveness of REAP in live media workflows. Explore objective and subjective quality assessment methods for media streams delivered using this standard.

The current/updated status of MPEG-DASH is shown in the figure below.

Video Coding Updates

In terms of video coding, two noteworthy updates are described here:

• Part 3 of MPEG-AI, ISO/IEC 23888-3 – Optimization of encoders and receiving systems for machine analysis of coded video content, reached Committee Draft Technical Report (CDTR) status
• Second edition of conformance and reference software for MPEG Immersive Video (MIV). This draft includes verified and validated conformance bitstreams and encoding and decoding reference software based on version 22 of the Test model for MPEG immersive video (TMIV). The test model, objective metrics, and some other tools are publicly available at https://gitlab.com/mpeg-i-visual.

Part 3 of MPEG-AI, ISO/IEC 23888-3: This new technical report on “optimization of encoders and receiving systems for machine analysis of coded video content” is based on software experiments conducted by JVET, focusing on optimizing non-normative elements such as preprocessing, encoder settings, and postprocessing. The research explored scenarios where video signals, decoded from bitstreams compliant with the latest video compression standard, ISO/IEC 23090-3 – Versatile Video Coding (VVC), are intended for input into machine vision systems rather than for human viewing. Compared to the JVET VVC reference software encoder, which was originally optimized for human consumption, significant bit rate reductions were achieved when machine vision task precision was used as the performance criterion.

The report will include an annex with example software implementations of these non-normative algorithmic elements, applicable to VVC or other video compression standards. Additionally, it will explore the potential use of existing supplemental enhancement information messages from ISO/IEC 23002-7 – Versatile supplemental enhancement information messages for coded video bitstreams – for embedding metadata useful in these contexts.

Research aspects: (1) Focus on optimizing video encoding for machine vision tasks by refining preprocessing, encoder settings, and postprocessing to improve bit rate efficiency and task precision, compared to traditional approaches for human viewing. (2) Examine the use of metadata, specifically SEI messages from ISO/IEC 23002-7, to enhance machine analysis of compressed video, improving adaptability, performance, and interoperability.

Subjective Quality Testing for Film Grain Synthesis

At the 148^th MPEG meeting , the MPEG Joint Video Experts Team (JVET) with ITU-T SG 16 (WG 5 / JVET) and MPEG Visual Quality Assessment (AG 5) conducted a formal expert viewing experiment to assess the impact of film grain synthesis on the subjective quality of video content. This evaluation specifically focused on film grain synthesis controlled by the Film Grain Characteristics (FGC) supplemental enhancement information (SEI) message. The study aimed to demonstrate the capability of film grain synthesis to mask compression artifacts introduced by the underlying video coding schemes.

For the evaluation, FGC SEI messages were adapted to a diverse set of video sequences, including scans of original film material, digital camera noise, and synthetic film grain artificially applied to digitally captured video. The subjective performance of video reconstructed from VVC and HEVC bitstreams was compared with and without film grain synthesis. The results highlighted the effectiveness of film grain synthesis, showing a significant improvement in subjective quality and enabling bitrate savings of up to a factor of 10 for certain test points.

This study opens several avenues for further research:

• Optimization of film grain synthesis techniques: Investigating how different grain synthesis methods affect the perceptual quality of video across a broader range of content and compression levels.
• Compression artifact mitigation: Exploring the interaction between film grain synthesis and specific types of compression artifacts, with a focus on improving masking efficiency.
• Adaptation of FGC SEI messages: Developing advanced algorithms for tailoring FGC SEI messages to dynamically adapt to diverse video characteristics, including real-time encoding scenarios.
• Bitrate savings analysis: Examining the trade-offs between bitrate savings and subjective quality across various coding standards and network conditions.

The 149th MPEG meeting will be held in Geneva, Switzerland from January 20-24, 2025. Click here for more information about MPEG meetings and their developments.

JPEG XE issues Call for Proposals on event-based vision representation

The 104th JPEG meeting was held in Sapporo, Japan from July 15 to 19, 2024. During this JPEG meeting, a Call for Proposals on event-based vision representation was launched for the creation of the first standardised representation of this type of data. This CfP addresses lossless coding, and aims to provide the first standard representation for event-based data that ensures interoperability between systems and devices.

Furthermore, the JPEG Committee pursued its work in various standardisation activities, particularly the development of new learning-based technology codecs and JPEG Trust.

The following summarises the main highlights of the 104th JPEG meeting.

• JPEG XE
• JPEG Trust
• JPEG AI
• JPEG Pleno Learning-based Point Cloud coding
• JPEG Pleno Light Field
• JPEG AIC
• JPEG Systems
• JPEG DNA
• JPEG XS
• JPEG XL

JPEG XE

The JPEG Committee continued its activity on JPEG XE and event-based vision. This activity revolves around a new and emerging image modality created by event-based visual sensors. JPEG XE is about the creation and development of a standard to represent events in an efficient way allowing interoperability between sensing, storage, and processing, targeting machine vision and other relevant applications. The JPEG Committee completed the Common Test Conditions (CTC) v2.0 document that provides the means to perform an evaluation of candidate technologies for efficient coding of events. The Common Test Conditions document also defines a canonical raw event format, a reference dataset, a set of key performance metrics and an evaluation methodology.

The JPEG Committee furthermore issued a Final Call for Proposals (CfP) on lossless coding for event-based data. This call marks an important milestone in the standardization process and the JPEG Committee is eager to receive proposals. The deadline for submission of proposals is set to March 31st of 2025. Standardization will start with lossless coding of events as this has the most imminent application urgency in industry. However, the JPEG Committee acknowledges that lossy coding of events is also a valuable feature, which will be addressed at a later stage.

Accompanying these two new public documents, a revised Use Cases and Requirements v2.0 document was also released to provide a formal definition for lossless coding of events that is used in the CTC and the CfP.

All documents are publicly available on jpeg.org. The Ad-hoc Group on event-based vision was re-established to continue work towards the 105th JPEG meeting. To stay informed about this activity please join the event-based vision Ad-hoc Group mailing list.

JPEG Trust

JPEG Trust provides a comprehensive framework for individuals, organizations, and governing institutions interested in establishing an environment of trust for the media that they use, and supports trust in the media they share. At the 104th meeting, the JPEG Committee produced an updated version of the Use Cases and Requirements for JPEG Trust (v3.0). This document integrates additional use cases and requirements related to authorship, ownership, and rights declaration. The JPEG Committee also requested a new Part to JPEG Trust, entitled “Media asset watermarking”. This new Part will define the use of watermarking as one of the available components of the JPEG Trust framework to support usage scenarios for content authenticity, provenance, integrity, labeling, and binding between JPEG Trust metadata and corresponding media assets. This work will focus on various types of watermarking, including explicit or visible watermarking, invisible watermarking, and implicit watermarking of the media assets with relevant metadata.

JPEG AI

At the 104th meeting, the JPEG Committee reviewed recent integration efforts, following the adoption of the changes in the past meeting and the creation of a new version of the JPEG AI verification model. This version reflects the JPEG AI DIS text and was thoroughly evaluated for performance and functionalities, including bitrate matching, 4:2:0 coding, region adaptive quantization maps, and other key features. JPEG AI supports a multi-branch coding architecture with two encoders and three decoders, allowing for six compatible combinations that have been jointly trained. The compression efficiency improvements range from 12% to 27% over the VVC Intra coding anchor, with decoding complexities between 8 to 215 kMAC/px.

The meeting also focused on Part 2: Profiles and Levels, which is moving to Committee Draft consultation. Two main concepts have been established: 1) the stream profile, defining a specific subset of the code stream syntax along with permissible parameter values, and 2) the decoder profile, specifying a subset of the full JPEG AI decoder toolset required to obtain the decoded image. Additionally, Part 3: Reference Software and Part 5: File Format will also proceed to Committee Draft consultation. Part 4 is significant as it sets the conformance points for JPEG AI compliance, and some preliminary experiments have been conducted in this area.

JPEG Pleno Learning-based Point Cloud coding

Learning-based solutions are the state of the art for several computer vision tasks, such as those requiring high-level understanding of image semantics, e.g., image classification, face recognition and object segmentation, but also 3D processing tasks, e.g. visual enhancement and super-resolution. Learning-based point cloud coding solutions have demonstrated the ability to achieve competitive compression efficiency compared to available conventional point cloud coding solutions at equivalent subjective quality. At the 104th meeting, the JPEG Committee instigated balloting for the Draft International Standard (DIS) of ISO/IEC 21794 Information technology — Plenoptic image coding system (JPEG Pleno) — Part 6: Learning-based point cloud coding. This activity is on track for the publication of an International Standard in January 2025. The 104th meeting also began an exploration into advanced point cloud coding functionality, in particular the potential for progressive decoding of point clouds.

JPEG Pleno Light Field

The JPEG Pleno Light Field effort has an ongoing standardization activity concerning a novel light field coding architecture that delivers a single coding mode to efficiently code light fields spanning from narrow to wide baselines. This novel coding mode is depth information agnostic resulting in significant improvement in compression efficiency. The first version of the Working Draft of the JPEG Pleno Part 2: Light Field Coding second edition (ISO/IEC 21794-2 2ED), including this novel coding mode, was issued during the 104th JPEG meeting in Sapporo, Japan.

The JPEG PLeno Model (JPLM) provides reference implementations for the standardized technologies within the JPEG Pleno framework, including the JPEG Pleno Part 2 (ISO/IEC 21794-2). Improvements to the JPLM have been implemented and tested, including the design of a more user-friendly platform.

The JPEG Pleno Light Field effort is also preparing standardization activities in the domains of objective and subjective quality assessment for light fields, aiming to address other plenoptic modalities in the future. During the 104th JPEG meeting in Sapporo, Japan, the collaborative subjective experiments aiming at exploring various aspects of subjective light field quality assessments were presented and discussed. The outcomes of these experiments will guide the decisions during the subjective quality assessment standardization process, which has issued its third Working Draft. A new version of a specialized tool for subjective quality evaluation, that supports these experiments, has also been released.

JPEG AIC

At its 104th meeting, the JPEG Committee reviewed results from previous Core Experiments that collected subjective data for fine-grained quality assessments of compressed images ranging from high to near-lossless visual quality. These crowdsourcing experiments used triplet comparisons with and without boosted distortions, as well as double stimulus ratings on a visual analog scale. Analysis revealed that boosting increased the precision of reconstructed scale values by nearly a factor of two. Consequently, the JPEG Committee has decided to use triplet comparisons in the upcoming AIC-3.

The JPEG Committee also discussed JPEG AIC Part 4, which focuses on objective image quality assessments for compressed images in the high to near-lossless quality range. This includes developing methods to evaluate the performance of such objective image quality metrics. A draft call for contributions is planned for January 2025.

JPEG Systems

At the 104th meeting Part 10 of JPEG Systems (ISO/IEC 19566-10), the JPEG Systems Reference Software, reached the IS stage. This first version of the reference software provides a reference implementation and reference dataset for the JPEG Universal Metadata Box Format (JUMBF, ISO/IEC 19566-5). Meanwhile, work is in progress to extend the reference software implementations of additional Parts, including JPEG Privacy and Security and JPEG 360.

JPEG DNA

JPEG DNA is an initiative aimed at developing a standard capable of representing bi-level, continuous-tone grey-scale, continuous-tone colour, or multichannel digital samples in a format using nucleotide sequences to support DNA storage. A Call for Proposals was published at the 99th JPEG meeting. Based on the performance assessments and descriptive analyses of the submitted solutions, the JPEG DNA Verification Model was created during the 102nd JPEG meeting. Several core experiments were conducted to validate this Verification Model, leading to the creation of the first Working Draft of JPEG DNA during the 103rd JPEG meeting.

The next phase of this work involves newly defined core experiments to enhance the rate-distortion performance of the Verification Model and its robustness to insertion, deletion, and substitution errors. Additionally, core experiments to test robustness against substitution and indel noise are conducted. A core experiment was also performed to integrate JPEG AI into the JPEG DNA VM, and quality comparisons have been carried out. A study on visual quality assessment of JPEG AI as an alternative to JPEG XL in the VM will be carried out.

In parallel, efforts are underway to improve the noise simulator developed at the 102nd JPEG meeting, enabling a more realistic assessment of the Verification Model’s resilience to noise. There is also ongoing exploration of the performance of different clustering and consensus algorithms to further enhance the VM’s capabilities.

JPEG XS

The core parts of JPEG XS 3rd edition were prepared for immediate publication as International Standards. This means that Part 1 of the standard – Core coding tools, Part 2 – Profiles and buffer models, and Part 3 – Transport and container formats, will be available before the end of 2024. Part 4 – Conformance testing is currently still under DIS ballot and it will be finalized in October 2024. At the 104th meeting, the JPEG Committee continued the work on Part 5 – Reference software. This part is currently at Committee Draft stage and the DIS is planned for October 2024. The reference software has a feature-complete decoder that is fully compliant with the 3rd edition. Work on the encoder is ongoing.

Finally, additional experimental results were presented on how JPEG XS can be used over 5G mobile networks for wireless transmission of low-latency and high quality 6K/8K 360 degree views with mobile devices and VR headsets. This work will be continued.

JPEG XL

Objective metrics results for HDR images were investigated (using among others the ColorVideoVDP metric), indicating very promising compression performance of JPEG XL compared to other codecs like AVIF and JPEG 2000. Both the libjxl reference software encoder and a simulated candidate hardware encoder were tested. Subjective experiments for HDR images are planned.

The second editions of JPEG XL Part 1 (Core coding system) and Part 2 (File format) are now ready for publication. The second edition of JPEG XL Part 3 (Conformance testing) has moved to the FDIS stage.

Final Quote

“The JPEG Committee has reached a new milestone by releasing a new Call for Proposals to code events. This call is aimed at creating the first International Standard to efficiently represent events, enabling interoperability between devices and systems that rely on event sensing.” said Prof. Touradj Ebrahimi, the Convenor of the JPEG Committee.