ATHENA Christian Doppler (CD) Laboratory

Data Compression Conference (DCC)

19-22 March 2024, Snowbird, Utah, USA

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Hadi Amirpour (AAU, Austria), Jingwen Zhu (University of Nantes, France), Raimund Schatz (AIT, Austria), Patrick Le Callet (University of Nantes, France), and Christian Timmerer (AAU, Austria)

Abstract: The evolving landscape of the delivery of multimedia content requires a deep understanding of how the design of the bitrate ladder (for HTTP adaptive streaming) influences cost and quality. This paper explores the use of Just Noticeable Differences (JND) to select bitrate-resolution pairs for constructing a bitrate ladder with respect to the proportion of satisfied user ratio (SUR). To expand the investigation to various codecs, first, a method is explained that transfers the JND points obtained through subjective testing from one codec (e.g., AVC) to other codecs (e.g., HEVC, VVC). This approach helps avoid the additional costs associated with conducting subjective tests to obtain JND points for a wide range of different codecs. To achieve this objective, we investigate the codec-agnostic nature of various video quality metrics, followed by the transfer of JND between two codecs, taking into account the most suitable codec-agnostic video quality metric. Secondly, we delve into the analysis of the bitrate cost of a given bitrate ladder from a JND perspective, i.e., as a function of the SUR. Among others, our experimental results demonstrate that to increase the SUR from 75% to 90%, it is necessary to double the video bitrate.

IEEE International Conference on

Acoustics, Speech, and Signal Processing (ICASSP)

14-19 April 2024, Seoul, Korea

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Hadi Amirpour (AAU, Austria), Jingwen Zhu (University of Nantes, France), Patrick Le Callet (University of Nantes, France), and Christian Timmerer (AAU, Austria)

Abstract: In HTTP Adaptive Streaming (HAS), a video is encoded at multiple bitrate-resolution pairs, referred to as representations, which enables users to choose the most suitable representation based on their network connection. To optimize the set of bitrate-resolution pairs and improve the Quality of Experience (QoE) for users, it is of utmost importance to measure the quality of the representations. VMAF is a highly reliable metric used in HAS to assess the quality of representations. However, in practice, using it for optimization can be a very time-consuming process, and it is infeasible for live streaming applications. To tackle its high complexity, our paper introduces a new method called VQM4HAS, which extracts low-complexity features including (i) video complexity features, (ii) bitstream features logged during the encoding process, and (iii) basic video quality metrics. These extracted features are then fed into a regression model to predict VMAF.
Our experimental results demonstrate that VQM4HAS achieves a high Pearson correlation coefficients (PCC) with VMAF from 0.95 to 0.96 depending on the resolution, but exhibits significantly less complexity, making it suitable for live streaming scenarios.

IEEE International Conference on

Acoustics, Speech, and Signal Processing (ICASSP)

14-19 April 2024, Seoul, Korea

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Mohammad Ghasempour (AAU, Austria), Hadi Amirpour (AAU, Austria), Mohammad Ghanbari (University of Essex, UK), and Christian Timmerer (AAU, Austria)

Abstract: With the ubiquity of video streaming, optimizing the delivery of video content while reducing energy consumption has become increasingly critical. Traditional adaptive streaming relies on a fixed set of bitrate-resolution pairs, known as bitrate ladders, for encoding. However, this one-size-fits-all approach is suboptimal for diverse video content. As a result, per-title encoding approaches dynamically select the bitrate ladder for each content. In this paper, we address the pressing issue of increasing energy consumption in video streaming by introducing GreenRes, a novel approach that goes beyond traditional quality-centric resolution selection. Instead, GreenRes considers both video quality and energy consumption to construct an optimal bitrate ladder tailored to the unique characteristics of each video content.
To achieve this, GreenRes, similar to per-title encoding, encodes each video content at various resolutions, each with a set of bitrates. It then establishes a maximum acceptable quality drop threshold and selects resolutions that not only maintain video quality above this threshold, but also minimize energy consumption. Our experimental results demonstrate a 30.82% reduction in energy consumption on average, while ensuring a maximum quality drop of 0.53 Video Multimethod Assessment Fusion (VMAF) points.

Elsevier Signal Processing

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Lingfeng Qu (Guangzhou University, China), Hui Lu (Guangzhou University, China), Peng Chen (Guangzhou University, China),  Hadi Amirpour (Alpen-Adria-Universität Klagenfurt, Austria), and Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Austria)

Abstract:

On behalf of ISO and IEC, this certificate is awarded to

Christian Timmerer

Project Editor in ISO/IEC|TC 1/SC 29/WG 3, MPEG Systems

In recognition of his excellent service to ISO/lEC JTC 1/SC 29, in particular, his exceptional contributions to the development of ISO/EC 23009-2:2020

April 2022

Klagenfurt, November 29, 2023

Reza Ebrahimi successfully defended his Master Thesis on “Quality of Experience Evaluation of Stall Events and Quality Switches in Game Streaming“.

Abstract: The exponential growth of computer game streaming has led to the development of Quality of Experience (QoE) metrics to evaluate user satisfaction and enjoyment during online gameplay and live streaming. Adaptive Bitrate (ABR) streaming is a recent technology that has been suggested to improve QoE. This method enhances the streaming experience, upholds visual quality, minimizes stall events, and boosts player retention. It achieves this by estimating network bottlenecks and selecting appropriate versions of the content that best match the available bandwidth rather than adjusting encoding parameters. To investigate the correlation between quality switching and stall events, a subjective test was conducted separately and comparatively with 71 participants. For more detailed and in-depth research, video games were analyzed with the Video Complexity Analyzer (VCA) tool and divided into three categories of different genres, camera view, and temporal complexity heatmap from the two sets of normal and action scenes. This study seeks to shed light on three unresolved issues pertinent to QoE in game streaming: (i) the user preferences towards quality switching and stall events across varied scenes and games, (ii) the user inclinations towards either a single, prolonged stall event or multiple, shorter stall events, and (iii) the impact of conspicuous quality switching on the user’s QoE. Results from the study provided valuable insights, both qualitatively and quantitatively. The study found a marked preference among users for quality switching over stall events across all types of game streaming, irrespective of the scene’s intensity. Furthermore, it was observed that multiple short-stall events were generally favored over a single long-stall event in streaming first-person shooting games. Interestingly, approximately half of the participants remained oblivious to quality switching during their game viewing sessions, and among those who noticed a change in quality, the alteration did not significantly impact their perceived QoE.