Special Issue "Multimedia Quality of Experience (QoE): Current Status and Future Direction"

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Techno-Social Smart Systems".

Deadline for manuscript submissions: closed (15 May 2020).

Special Issue Editors

Dr. Chaminda Hewage
Website
Guest Editor
Cardiff School of Technologies (CST), Cardiff Metropolitan University, Cardiff CF5 2YB, UK
Interests: Quality of Experience (QoE); multimeida; security
Dr. Erhan Ekmekcioglu
Website
Guest Editor
Institute for Digital Technologies, Loughborough University London, London E15 2GZ, UK
Interests: video processing; streaming; Quality of Experience; affective computing
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Special Issue Information

Dear Colleagues,

Quality of Experience (QoE) can be defined as the overall delight or annoyance of the user of an application or service. Typically, Multimedia QoE expected to offer improved user satisfaction from the audio-visual channels that the users interact. Even though a significant number of novel multimedia applications are emerging, it is a challenge to provide better multimedia QoE for the end user. As a result, most of novel multimedia applications fail to provide a minimum level of QoE required for end users to keep them engaged with the content. This is mainly due to the complexity of the content representation, processing, communication, security and visualisation. Therefore, in order to design QoE proofed multimedia application, researchers need to overcome five sets of challenges. The advancement of technology and multi-disciplinary research have enabled some multimedia applications to provide end-user satisfaction by overcoming technological and social barriers. It is interesting to explore how well novel multimedia applications meet end-user expectations or satisfy user QoE where the use of objective approaches of measuring quality (e.g., QoS) is no longer acceptable.

Original contributions showing practical approaches are also welcome. Potential topics include but are not limited to the following:

  • multimedia quality of experience (QoE);
  • QoE evaluation in immersive multimedia, VR, AR, and novel storytelling environments;
  • QoE evaluation in mulsemedia (or multi-sensory) environments;
  • data-driven approaches for QoE evaluation and optimisation;
  • QoE prediction from auxiliary and wearable sensors;
  • psychophysiological methods for quality of experience research;
  • next generation QoE driven multimedia applications (e.g., 5G multimedia applications);
  • human visual system modelling;
  • advanced methods of multimedia representation, processing, visualization and interaction;
  • multimedia privacy and security;
  • QoE standardization activities.

Dr. Chaminda Hewage
Dr. Erhan Ekmekcioglu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (6 papers)

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Editorial

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Open AccessEditorial
Multimedia Quality of Experience (QoE): Current Status and Future Direction
Future Internet 2020, 12(7), 121; https://doi.org/10.3390/fi12070121 - 20 Jul 2020
Abstract
Quality of Experience (QoE) is becoming an important factor of User-Centred Design (UCD). The deployment of pure technical measures such as Quality of Service (QoS) parameters to assess the quality of multimedia applications is phasing out due to the failure of those methods [...] Read more.
Quality of Experience (QoE) is becoming an important factor of User-Centred Design (UCD). The deployment of pure technical measures such as Quality of Service (QoS) parameters to assess the quality of multimedia applications is phasing out due to the failure of those methods to quantify true user satisfaction. Though significant research results and several deployments have occurred and been realized over the last few years, focusing on QoE-based multimedia technologies, several issues both of theoretical and practical importance remain open. Accordingly, the papers of this Special Issue are significant contribution samples within the general ecosystem highlighted above, ranging from QoE in the capture, processing and consumption of next-generation multimedia applications. In particular, a total of five excellent articles have been accepted, following a rigorous review process, which address many of the aforementioned challenges and beyond. Full article

Research

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Open AccessArticle
A Decoding-Complexity and Rate-Controlled Video-Coding Algorithm for HEVC
Future Internet 2020, 12(7), 120; https://doi.org/10.3390/fi12070120 - 16 Jul 2020
Cited by 1
Abstract
Video playback on mobile consumer electronic (CE) devices is plagued by fluctuations in the network bandwidth and by limitations in processing and energy availability at the individual devices. Seen as a potential solution, the state-of-the-art adaptive streaming mechanisms address the first aspect, yet [...] Read more.
Video playback on mobile consumer electronic (CE) devices is plagued by fluctuations in the network bandwidth and by limitations in processing and energy availability at the individual devices. Seen as a potential solution, the state-of-the-art adaptive streaming mechanisms address the first aspect, yet the efficient control of the decoding-complexity and the energy use when decoding the video remain unaddressed. The quality of experience (QoE) of the end-users’ experiences, however, depends on the capability to adapt the bit streams to both these constraints (i.e., network bandwidth and device’s energy availability). As a solution, this paper proposes an encoding framework that is capable of generating video bit streams with arbitrary bit rates and decoding-complexity levels using a decoding-complexity–rate–distortion model. The proposed algorithm allocates rate and decoding-complexity levels across frames and coding tree units (CTUs) and adaptively derives the CTU-level coding parameters to achieve their imposed targets with minimal distortion. The experimental results reveal that the proposed algorithm can achieve the target bit rate and the decoding-complexity with 0.4% and 1.78% average errors, respectively, for multiple bit rate and decoding-complexity levels. The proposed algorithm also demonstrates a stable frame-wise rate and decoding-complexity control capability when achieving a decoding-complexity reduction of 10.11 (%/dB). The resultant decoding-complexity reduction translates into an overall energy-consumption reduction of up to 10.52 (%/dB) for a 1 dB peak signal-to-noise ratio (PSNR) quality loss compared to the HM 16.0 encoded bit streams. Full article
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Open AccessFeature PaperArticle
No-Reference Depth Map Quality Evaluation Model Based on Depth Map Edge Confidence Measurement in Immersive Video Applications
Future Internet 2019, 11(10), 204; https://doi.org/10.3390/fi11100204 - 20 Sep 2019
Cited by 3
Abstract
When it comes to evaluating perceptual quality of digital media for overall quality of experience assessment in immersive video applications, typically two main approaches stand out: Subjective and objective quality evaluation. On one hand, subjective quality evaluation offers the best representation of perceived [...] Read more.
When it comes to evaluating perceptual quality of digital media for overall quality of experience assessment in immersive video applications, typically two main approaches stand out: Subjective and objective quality evaluation. On one hand, subjective quality evaluation offers the best representation of perceived video quality assessed by the real viewers. On the other hand, it consumes a significant amount of time and effort, due to the involvement of real users with lengthy and laborious assessment procedures. Thus, it is essential that an objective quality evaluation model is developed. The speed-up advantage offered by an objective quality evaluation model, which can predict the quality of rendered virtual views based on the depth maps used in the rendering process, allows for faster quality assessments for immersive video applications. This is particularly important given the lack of a suitable reference or ground truth for comparing the available depth maps, especially when live content services are offered in those applications. This paper presents a no-reference depth map quality evaluation model based on a proposed depth map edge confidence measurement technique to assist with accurately estimating the quality of rendered (virtual) views in immersive multi-view video content. The model is applied for depth image-based rendering in multi-view video format, providing comparable evaluation results to those existing in the literature, and often exceeding their performance. Full article
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Open AccessArticle
Quality of Experience (QoE)-Aware Fast Coding Unit Size Selection for HEVC Intra-Prediction
Future Internet 2019, 11(8), 175; https://doi.org/10.3390/fi11080175 - 11 Aug 2019
Cited by 2
Abstract
The exorbitant increase in the computational complexity of modern video coding standards, such as High Efficiency Video Coding (HEVC), is a compelling challenge for resource-constrained consumer electronic devices. For instance, the brute force evaluation of all possible combinations of available coding modes and [...] Read more.
The exorbitant increase in the computational complexity of modern video coding standards, such as High Efficiency Video Coding (HEVC), is a compelling challenge for resource-constrained consumer electronic devices. For instance, the brute force evaluation of all possible combinations of available coding modes and quadtree-based coding structure in HEVC to determine the optimum set of coding parameters for a given content demand a substantial amount of computational and energy resources. Thus, the resource requirements for real time operation of HEVC has become a contributing factor towards the Quality of Experience (QoE) of the end users of emerging multimedia and future internet applications. In this context, this paper proposes a content-adaptive Coding Unit (CU) size selection algorithm for HEVC intra-prediction. The proposed algorithm builds content-specific weighted Support Vector Machine (SVM) models in real time during the encoding process, to provide an early estimate of CU size for a given content, avoiding the brute force evaluation of all possible coding mode combinations in HEVC. The experimental results demonstrate an average encoding time reduction of 52.38%, with an average Bjøntegaard Delta Bit Rate (BDBR) increase of 1.19% compared to the HM16.1 reference encoder. Furthermore, the perceptual visual quality assessments conducted through Video Quality Metric (VQM) show minimal visual quality impact on the reconstructed videos of the proposed algorithm compared to state-of-the-art approaches. Full article
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Open AccessArticle
Modeling of Cumulative QoE in On-Demand Video Services: Role of Memory Effect and Degree of Interest
Future Internet 2019, 11(8), 171; https://doi.org/10.3390/fi11080171 - 04 Aug 2019
Cited by 2
Abstract
The growing demand on video streaming services increasingly motivates the development of a reliable and accurate models for the assessment of Quality of Experience (QoE). In this duty, human-related factors which have significant influence on QoE play a crucial role. However, the complexity [...] Read more.
The growing demand on video streaming services increasingly motivates the development of a reliable and accurate models for the assessment of Quality of Experience (QoE). In this duty, human-related factors which have significant influence on QoE play a crucial role. However, the complexity caused by multiple effects of those factors on human perception has introduced challenges on contemporary studies. In this paper, we inspect the impact of the human-related factors, namely perceptual factors, memory effect, and the degree of interest. Based on our investigation, a novel QoE model is proposed that effectively incorporates those factors to reflect the user’s cumulative perception. Evaluation results indicate that our proposed model performed excellently in predicting cumulative QoE at any moment within a streaming session. Full article
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Open AccessArticle
The Effects of the Floating Action Button on Quality of Experience
Future Internet 2019, 11(7), 148; https://doi.org/10.3390/fi11070148 - 06 Jul 2019
Cited by 1
Abstract
Google’s Material Design, created in 2014, led to the extended application of floating action buttons (FAB) in user interfaces of web pages and mobile applications. FAB’s roll is to trigger an activity either on the present screen, or it can play out an [...] Read more.
Google’s Material Design, created in 2014, led to the extended application of floating action buttons (FAB) in user interfaces of web pages and mobile applications. FAB’s roll is to trigger an activity either on the present screen, or it can play out an activity that makes another screen. A few specialists in user experience (UX) and user interface (UI) design are sceptical regarding the usability of FAB in the interfaces of both web pages and mobile applications. They claim that the use of FAB easily distracts users and that it interferes with using other important functions of the applications, and it is unusable in applications designed for iOS systems. The aim of this paper is to investigate by an experiment the quality of experience (QoE) of a static and animated FAB and compare it to the toolbar alternative. The experimental results of different testing methods rejected the hypothesis that the usage and animation of this UI element has a positive influence on the application usability. However, its static and animated utilization enhanced the ratings of hedonic and aesthetic features of the user experience, justifying the usage of this type of button. Full article
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