QoMEX’23: Impact of Quality and Distance on the Perception of Point Clouds in Mixed Reality

The 15th International Conference on Quality of Multimedia Experience (QoMEX)

June 20-22, 2023 – Ghent, Belgium

https://qomex2023.itec.aau.at/

[PDF][Slides]

Minh Nguyen (Alpen-Adria-Universität Klagenfurt), Shivi Vats (Alpen-Adria-Universität Klagenfurt), Sam Van Damme (Ghent University – imec), Jeroen van der Hooft (Ghent University – imec), Maria Torres Vega (Ghent University – imec), Tim Wauters (Ghent University – imec), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)

Abstract: Point Cloud (PC) streaming has recently attracted research attention as it has the potential to provide six degrees of freedom (6DoF), which is essential for truly immersive media. PCs require high-bandwidth connections, and adaptive streaming is a promising solution to cope with fluctuating bandwidth conditions. Thus, understanding the impact of different factors in adaptive streaming on the Quality of Experience (QoE) becomes fundamental. Mixed Reality (MR) is a novel technology and has recently become popular. However, quality evaluations of PCs in MR environments are still limited to static images. In this paper, we perform a subjective study on four impact factors on the QoE of PC video sequences in MR conditions, including quality switches, viewing distance, and content characteristics. The experimental results show that these factors significantly impact QoE. The QoE decreases if the sequence switches to lower quality and/or is viewed at a shorter distance, and vice versa. Additionally, the end user might not distinguish the quality differences between two quality levels at a specific viewing distance. Regarding content characteristics, objects with lower contrast seem to provide better quality scores.

Index Terms—Point Clouds, Quality of Experience, Subjective Tests, Mixed Reality

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QoMEX’23: A Platform for Subjective Quality Assessment in Mixed Reality Environments

The 15th International Conference on Quality of Multimedia Experience (QoMEX)

June 20-22, 2023 – Ghent, Belgium

https://qomex2023.itec.aau.at/

[PDF][Slides]

Minh Nguyen (Alpen-Adria-Universität Klagenfurt)Shivi Vats (Alpen-Adria-Universität Klagenfurt), Sam Van Damme (Ghent University – imec), Jeroen van der Hooft (Ghent University – imec), Maria Torres Vega (Ghent University – imec), Tim Wauters (Ghent University – imec), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)

Abstract: 3D objects are important components in Mixed Reality (MR) environments as they allow users to inspect and interact with them in a six degrees of freedom (6DoF) system. Point clouds (PCs) and meshes are two common 3D object representations that can be compressed to reduce the delivered data at the cost of quality degradation. In addition, as the end users can move around in 6DoF applications, the viewing distance can vary. Quality assessment is necessary to evaluate the impact of the compressed representation and viewing distance on the Quality of Experience (QoE) of end users. This paper presents a demonstrator for subjective quality assessment of dynamic PC and mesh objects under different conditions in MR environments. Our platform allows conducting subjective tests to evaluate various QoE influence factors, including encoding parameters, quality switching, viewing distance, and content characteristics, with configurable settings for these factors.

Index Terms—Point Clouds, Subjective Test Platform, Quality of Experience, Mixed Reality

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QoE- and Energy-aware Content Consumption For HTTP Adaptive Streaming

14th ACM Multimedia Systems Conference (MMSys)

7 – 10 June 2023 | Vancouver, BC, Canada

Conference Website

[PDF][Slides][Poster]

Daniele Lorenzi (AAU, Austria)

Abstract: Video streaming services account for the majority of today’s traffic on the Internet, and according to recent studies, this share is expected to continue growing. Given this broad utilization, research in video streaming is recently moving towards energy-aware approaches, which aim at reducing the energy consumption of the devices involved in the streaming process. On the other side, the perception of quality delivered to the user plays an important role, and the advent of HTTP Adaptive Streaming (HAS) changed the way quality is perceived. The focus is not any more exclusively on the Quality of Service (QoS) but rather oriented towards the Quality of Experience (QoE) of the user taking part in the streaming session. Therefore video streaming services need to develop Adaptive BitRate (ABR) techniques to deal with different network conditions on the client side or appropriate end-to-end strategies to provide high QoE to the users. The scope of this doctoral study is within the end-to-end environment with a focus on the end-users domain, referred to as the player environment, including video content consumption and interactivity. This thesis aims to investigate and develop different techniques to increase the delivered QoE to the users and minimize the energy consumption of the end devices in HAS context. We present four main research questions to target the related challenges in the domain of content consumption for HAS systems.

Keywords: Multi-codec, HTTP/3, machine learning, green computing, HAS

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Just Noticeable Difference-aware Per-Scene Bitrate-laddering for Adaptive Video Streaming

IEEE International Conference on Multimedia and Expo (ICME), 2023

10-14 July 2023, Brisbane, Australia

[PDF] [Slides]

Vignesh V Menon (Alpen-Adria-Universität Klagenfurt), Jingwen Zhu (Nantes Universite), Prajit T Rajendran (Universite Paris-Saclay), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Patrick Le Callet (Nantes Universite),  and Christian Timmerer (Alpen-Adria-Universität Klagenfurt).

Abstract:

In video streaming applications, a fixed set of bitrate-resolution pairs (known as a bitrate ladder) is typically used during the entire streaming session. However, an optimized bitrate ladder per scene may result in (i) decreased storage or delivery costs or/and (ii) increased Quality of Experience. This paper introduces a Just Noticeable Difference (JND)-aware per-scene bitrate ladder prediction scheme (JASLA) for adaptive video-on-demand streaming applications. JASLA predicts jointly optimized resolutions and corresponding constant rate factors (CRFs) using spatial and temporal complexity features for a given set of target bitrates for every scene, which yields an efficient constrained Variable Bitrate encoding. Moreover, bitrate-resolution pairs that yield distortion lower than one JND are eliminated. Experimental results show that, on average, JASLA yields bitrate savings of 34.42% and 42.67% to maintain the same PSNR and VMAF, respectively, compared to the reference HTTP Live Streaming (HLS) bitrate ladder Constant Bitrate encoding using x265 HEVC encoder, where the maximum resolution of streaming is Full HD (1080p). Moreover, a 54.34% average cumulative decrease in storage space is observed.

JASLA architecture.

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Optimizing Video Streaming for Sustainability and Quality: The Role of Preset Selection in Per-Title Encoding

IEEE International Conference on Multimedia and Expo (ICME)

10-14 July 2023, Brisbane, Australia

[PDF]

Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Vignesh V Menon (Alpen-Adria-Universität Klagenfurt), Samira Afzal (Alpen-Adria-Universität Klagenfurt), Radu Prodan (Alpen-Adria-Universität Klagenfurt),  and Christian Timmerer (Alpen-Adria-Universität Klagenfurt)

Abstract: HTTP Adaptive Streaming (HAS) methods divide a video into smaller segments, encoded at multiple pre-defined bitrates to construct a bitrate ladder. Bitrate ladders are usually optimized per title over several dimensions, such as bitrate, resolution, and framerate. This paper adds a new dimension to the bitrate ladder by considering the energy consumption of the encoding process. Video encoders often have multiple pre-defined presets to balance the trade-off between encoding time, energy consumption, and compression efficiency. Faster presets disable certain coding tools defined by the codec to reduce the encoding time at the cost of reduced compression efficiency. Firstly, this paper evaluates the energy consumption and compression efficiency of different x265 presets for 500 video sequences. Secondly, optimized presets are selected for various representations in a bitrate ladder based on the results to guarantee a minimal drop in video quality while saving energy. Finally, a new per-title model, which optimizes the trade-off between compression efficiency and energy consumption, is proposed. The experimental results show that decreasing the VMAF score by 0.15 and 0.39 while choosing an optimized preset results in encoding energy savings of 70% and 83%, respectively.

Keywords: Bitrate ladder, per-title encoding, green video streaming, energy efficiency.

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VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing Instances

GMSys 2023: First International ACM Green Multimedia Systems Workshop

7 – 10 June 2023 | Vancouver, Canada

Conference Website

[PDF][Slides]

Samira Afzal (Alpen-Adria-Universität Klagenfurt), Narges Mehran (Alpen-Adria-Universität Klagenfurt), Sandro Linder (Bitmovin), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), and Radu Prodan (Alpen-Adria-Universität Klagenfurt)

Abstract: The considerable surge in energy consumption within data centers can be attributed to the exponential rise in demand for complex computing workflows and storage resources. Video streaming applications are both compute and storage-intensive and account for the majority of today’s internet services. In this work, we designed a video encoding application consisting of codec, bitrate, and resolution set for encoding a video segment. Then, we propose VE-Match, a matching-based method to schedule video encoding applications on both Cloud and Edge resources to optimize costs and energy consumption. Evaluation results on a real computing testbed federated between Amazon Web Services (AWS) EC2 Cloud instances and the Alpen-Adria University (AAU) Edge server reveal that VE-Match achieves lower costs by 17%-78% in the cost-optimized scenarios compared to the energy-optimized and tradeoff between cost and energy. Moreover, VE-Match improves the video encoding energy consumption by 38%-45% and gCO2 emission by up to 80 % in the energy-optimized scenarios compared to the cost-optimized and tradeoff between cost and energy.

Keywords: Video encoding, Cloud and Edge computing, energy consumption, CO2 emission, scheduling.

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HTTP Adaptive Streaming – Quo Vadis? (2023)

IEEE ComSoc MMTC Distinguished Lecture Series

Speaker: Prof. Christian Timmerer, Alpen-Adria-Universität Klagenfurt (AAU), Austria

Date/Time: Thursday, Apr 20, 2023, 10:00 AM Pacific Time (US and Canada), CET Time 7:00 PM Austria
Title: HTTP Adaptive Streaming (HAS) — Quo Vadis? (2023; for the 2021 version, see here)

Abstract: Video traffic on the Internet is constantly growing; networked multimedia applications consume a predominant share of the available Internet bandwidth. A major technical breakthrough and enabler in multimedia systems research and of industrial networked multimedia services certainly was the HTTP Adaptive Streaming (HAS) technique. This resulted in the standardization of MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) which, together with HTTP Live Streaming (HLS), is widely used for multimedia delivery in today’s networks. Existing challenges in multimedia systems research deal with the trade-off between (i) the ever-increasing content complexity, (ii) various requirements with respect to time (most importantly, latency), and (iii) quality of experience (QoE). Optimizing towards one aspect usually negatively impacts at least one of the other two aspects if not both. This situation sets the stage for our research work in the ATHENA Christian Doppler (CD) Laboratory (Adaptive Streaming over HTTP and Emerging Networked Multimedia Services; https://athena.itec.aau.at/), jointly funded by public sources and industry. In this talk, we will present selected novel approaches and research results of the first year of the ATHENA CD Lab’s operation. We will highlight HAS-related research on (i) multimedia content provisioning (machine learning for video encoding); (ii) multimedia content delivery (support of edge processing and virtualized network functions for video networking); (iii) multimedia content consumption and end-to-end aspects (player-triggered segment retransmissions to improve video playout quality); and (iv) novel QoE investigations (adaptive point cloud streaming). We will also put the work into the context of international multimedia systems research.

Biography: Christian Timmerer is a full professor of computer science at Alpen-Adria-Universität Klagenfurt (AAU), Institute of Information Technology (ITEC) and he is the director of the Christian Doppler (CD) Laboratory ATHENA (https://athena.itec.aau.at/). His research interests include multimedia systems, immersive multimedia communication, streaming, adaptation, and quality of experience where he co-authored seven patents and more than 300 articles. He was the general chair of WIAMIS 2008, QoMEX 2013, MMSys 2016, and PV 2018 and has participated in several EC-funded projects, notably DANAE, ENTHRONE, P2P-Next, ALICANTE, SocialSensor, COST IC1003 QUALINET, ICoSOLE, and SPIRIT. He also participated in ISO/MPEG work for several years, notably in the area of MPEG-21, MPEG-M, MPEG-V, and MPEG-DASH where he also served as standard editor. In 2012 he cofounded Bitmovin (http://www.bitmovin.com/) to provide professional services around MPEG-DASH where he holds the position of the Chief Innovation Officer (CIO) –- Head of Research and Standardization. Further information at http://timmerer.com.

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