ABSTRACT
In this chapter, research about the assessment of video quality for gaming content will be provided. At first, a dataset that was used for the development of the ITU-T Rec. G.1072 will be presented. The dataset was created in a laboratory environment using the passive test paradigm described in Chap. 3. Next, some results of the collected video quality ratings will be illustrated. While QoE assessment studies traditionally make use of controlled laboratory environments, there are also other possibilities to conduct user studies without a laboratory environment. Especially during the COVID-19 pandemic, which prevented many researchers from performing lab studies, the concept of supervised and unsupervised remote studies got lots of attention. By using such a remote study design, two studies assessing video quality ratings of similar conditions as in the previously mentioned dataset were conducted. These two studies allow to address three research topics that will be the focus of the remainder of this chapter. At first, it will be investigated whether video quality ratings obtained using the remote study design are comparable to those collected in the lab environment. Second, a comparison between video quality ratings collected using a stimulus duration of 20 s instead of 30 s will be performed, which tries to answer whether it is enough to use a shorter stimulus duration as proposed in ITU-T Rec. P.809. Lastly, the differences between using a discrete 5-point ACR scale and the extended continuous 7-point scales will be investigated. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
During the COVID-19 lockdowns in South Africa undergraduate laboratory sessions were forbidden, in turn, video-based tutorials were proposed as a tentative solution to address the lack of in-person practical demonstration sessions. Five videos were filmed on electrical engineering topics, uploaded, and then publicly shared on YouTube. An investigation was then conducted as to whether videos may be useful for the teaching of practical engineering content in the university context. This article is a report back on the findings of using YouTube as a platform for sharing and evaluating engineering educational practical tutorial videos. The gaol of this article is to introduce YouTube's social media analytics as a tool for educators to evaluate their educational videos. The findings suggest that educators may consider evaluating their videos using social media analytics, but these analytics should be reviewed critically and should comprise of several metrics measured temporally. Understanding YouTube's recommender system and its influence on the platform is also an important factor in evaluating one's video content. © 2022 IEEE.
ABSTRACT
Cloud performing arts businesses has been accelerated by the advent of the 5G era and the COVID-19 pandemic, so there is a growing demand for a quality of experience (QoE) predictive model. However, QoE is a time series factor with nonlinear relationship influence, including subjective and objective factors named Quality of Service(QoS), which leads to a high complex prediction. To solve this problem, existing studies have utilized Long Short-Term Memory Networks (LSTM) and Convolutional Neural Networks (CNN) to effectively capture this kind of complex dependency, respectively, to obtain excellent QoE prediction accuracy. However, they can not take into account the accuracy and computational efficiency at the same time. So we proposes CGRU-QoE, that is, using CNN to extract global information, using the variant of LSTM-Gate Recurrent Unit (GRU) to extract context information, and then following the Attention Mechanism. In addition, we introduced a new input factor representing bitrate. The proposed method is mainly validated in the LFOVIA database and is superior to the baseline method in terms of prediction accuracy and computational complexity. © 2022 IEEE.
ABSTRACT
CONTEXT Video usage in higher education has increased markedly over many years, but ongoing disruptions caused by the COVID-19 pandemic have accelerated this trend. Consequently, a growing number of educators are grappling with how to best approach video production. Although a range of factors such as video quality, video length, and the presenters' style are known to influence student engagement with videos, more research is needed to understand the extent to which these factors impact, particularly in higher education. This can support educators producing video content that prioritises those aspects which are most critical. PURPOSE This research seeks to understand what factors are most influential on students' decisions to engage versus disengage with video resources in the higher education context. This aims to develop a series of recommendations for educators to focus on when producing videos for inclusion in higher engineering education courses. APPROACH This research considers two mechanical engineering courses taught at different Australian universities. These courses used videos as the primary delivery mode during Semester 2 (July to November) of 2020. Approximately half of each course explicitly applied production recommendations of a highly influential study. Students were surveyed at the end of the semester about their engagement preferences. OUTCOMES The quality of the presenter's explanations and their enthusiasm in delivery were the most important factors influencing engagement, while seeing the presenter was least important. Video length and quality were more likely to cause disengagement when poor, than drive engagement when done well. CONCLUSIONS Characteristics of the presenter's delivery (that is the quality of their explanations and their enthusiasm) are more influential in producing engaging video content than technological choices relating to the video capture and length. Therefore, educators should seek to prioritise the quality of their explanations and their stage presence, before working to improve the video/audio capture quality and reducing video durations. Including the face of the instructor in educational videos has little impact on students' usage decisions. Copyright © J. Khanna and A. Bigham, 2021.
ABSTRACT
Video conferencing, which includes both video and audio content, has contributed to dramatic increases in Internet traffic, as the COVID-19 pandemic forced millions of people to work and learn from home. Global Internet traffic of video conferencing has dramatically increased Because of this, efficient and accurate video quality tools are needed to monitor and perceptually optimize telepresence traffic streamed via Zoom, Webex, Meet, etc. However, existing models are limited in their prediction capabilities on multi-modal, live streaming telepresence content. Here we address the significant challenges of Telepresence Video Quality Assessment (TVQA) in several ways. First, we mitigated the dearth of subjectively labeled data by collecting ∼ 2k telepresence videos from different countries, on which we crowdsourced ∼ 80k subjective quality labels. Using this new resource, we created a first-of-a-kind online video quality prediction framework for live streaming, using a multi-modal learning framework with separate pathways to compute visual and audio quality predictions. Our all-in-one model is able to provide accurate quality predictions at the patch, frame, clip, and audiovisual levels. Our model achieves state-of-the-art performance on both existing quality databases and our new TVQA database, at a considerably lower computational expense, making it an attractive solution for mobile and embedded systems. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
In this chapter, research about the assessment of video quality for gaming content will be provided. At first, a dataset that was used for the development of the ITU-T Rec. G.1072 will be presented. The dataset was created in a laboratory environment using the passive test paradigm described in Chap. 3. Next, some results of the collected video quality ratings will be illustrated. While QoE assessment studies traditionally make use of controlled laboratory environments, there are also other possibilities to conduct user studies without a laboratory environment. Especially during the COVID-19 pandemic, which prevented many researchers from performing lab studies, the concept of supervised and unsupervised remote studies got lots of attention. By using such a remote study design, two studies assessing video quality ratings of similar conditions as in the previously mentioned dataset were conducted. These two studies allow to address three research topics that will be the focus of the remainder of this chapter. At first, it will be investigated whether video quality ratings obtained using the remote study design are comparable to those collected in the lab environment. Second, a comparison between video quality ratings collected using a stimulus duration of 20 s instead of 30 s will be performed, which tries to answer whether it is enough to use a shorter stimulus duration as proposed in ITU-T Rec. P.809. Lastly, the differences between using a discrete 5-point ACR scale and the extended continuous 7-point scales will be investigated. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The Artful Craft of Science (TACoS) is a week-long summer camp that the University of Wyoming has provided annually for up to 80 upcoming 5th and 6th graders since 2015. The program includes a variety of activities in science, technology, engineering, and mathematics (STEM), including a five-day introductory computer science (CS) class. In 2020 and 2021, TACoS ran virtually due to COVID-19, revealing a unique opportunity to compare two instances of the CS section of the program. This study focuses on answering two questions: 1) How does video quality impact student participation and engagement;and 2) How does the length of time that content is accessible affect how students engage with course material? Both virtual years (Summers 2020 and 2021), the CS program included five 20-30-minute videos, a corresponding website for students to follow, and physical components that were mailed to each student prior to the course. After the first year (Summer 2020), improvements were made to the CS course presentation including attention to video quality, fresh course content for repeat-attendees, and further streamlined lesson plans. In the second virtual year (Summer 2021), students were given access to course material for a longer amount of time, as content remained available for a month instead of only during the camp week. Over both virtual years, viewership data was collected from each video including the number of views per activity, the average view duration, the audience retention rate across each video, the average views per viewer, and the lifetime watch time for each video. A total of 37 (46%) parent evaluation reviews (including perspectives of their students) of the TACoS program were collected, providing insight on the overall impressions of the camp, the CS program specifically, the students' favorite project/course within TACoS, the course completion rate, the ranked comparison of parents' time spent helping their child with each TACoS program, and general parent feedback. Findings show that there was improvement in the video content which could have invited more participation in the project/course and higher student engagement with the project/course material in the second virtual year. © American Society for Engineering Education, 2022.
ABSTRACT
The turn of the decade introduced a new era of global pandemics to the world through the appearance of COVID-19, which is still an active crisis at the time of this paper. As a countermeasure, the phenomena of home office and online education became not only widely available, but also mandatory in many countries. However, the performance, reliability and general usability of such real-time activities may be severely affected by unfavorable network conditions. In both contexts, content sharing is now a common practice, and the success of the related use cases may fundamentally depend on it. In this paper, we present our surveys and subjective studies on the Quality of Experience of content sharing in online education and online meetings. A total of 6 surveys and 5 experiments are detailed, addressing topics of student experience, user interface settings, sharing options of lecturers and employees of the private sector, the perceivable effects of network impairments and the related long-term adaptation, the rubber band effect of slide sharing, the overall perceived quality and the separate quality aspects of media loading times, and the preference between visual quality, average frame rate and frame rale uniformity. The findings of the subjective studies do not characterize the use cases of the investigated topics on a general, widely-applicable level, as only a single online platform is involved throughout the experiments. However, their experimental configurations are reinforced by comprehensive surveys and many results indicate statistically significant differences between the selected lest conditions.
ABSTRACT
This paper provides a subjective analysis of streaming video to understand human visual Quality of Experience (QoE). The emergence of the Corona pandemic has prompted a rise in demand for internet services, particularly for video streaming. A limited number of companies in Europe choose to reduce video transmission quality to escape Internet strain. The QoE markers are defined as either satisfactory if the video loads in less than 10 seconds and plays out efficiently or undesirable if the loading time is above 10 seconds or the playout suffers from stands. Online media will display various kinds of high motion sports and music videos. Such metrics would enable internet providers to assess the degree to which the QoE of video streaming customers can decline under bad network conditions. Video quality is influenced by consumer behavior and content and network and device efficiency. A more significant number of content types would help us to study human viewer behavior better. Network providers typically do not see this kind of traffic. QoE is now believed to be an essential aspect of the reactive traffic control mechanism within network operators. The researcher looked for the best to create a database that contains as many subject forms as possible. The mean opinion score (MOS) has an exponential relationship with the video playout's number of stalls. Today's Global Adaptive Streaming over HTTP (DASH) definition to distribute the content-based streaming services employ differential bitrate techniques. QoE tracking often considers a variety of video QoE influence factors (IFs) and contableuration schemes. Multimedia information QoE can be assessed using subjective or objective methods. © 2021 IEEE
ABSTRACT
With increasing numbers of laparoscopic hysterectomies, surgical trainees are compelled to learn more about endoscopy. Owing to coronavirus disease-related social distancing requirements, online education has gained prominence. Here, we aimed to investigate the laparoscopic hysterectomy video quality on YouTube using the LAParoscopic surgery Video Educational GuidelineS (LAP-VEGaS). YouTube was searched on June 7, 2020 using 'laparoscopic hysterectomy'. Three examiners evaluated videos using Global Operative Assessment of Laparoscopic Skills (GOALS). Subsequently, videos were assessed for their conformity to the LAP-VEGaS and LAP-VEGaS Video Assessment Tool. Interobserver reliability was estimated using intraclass coefficients and Cronbach's alpha. Cochran's Q test was used to determine correlations among quantitative data. The median GOALS score was 21.50. The observers' GOALS scores were significantly correlated. The results showed low conformity to the LAP-VEGaS. YouTube is the most used platform among trainees. The low YouTube video educational quality highlights the necessity for peer review, as trainees increasingly seek such resources during the pandemic.IMPACT STATEMENTWhat is already known on this subject? YouTube is the most commonly used online resource for educational material among surgical trainees. Online videos usually do not undergo a peer-review process. The LAParoscopic surgery Video Educational GuidelineS (LAP-VEGaS) may be used to assess the educational quality of surgical videos.What do the results of this study add? To our knowledge, this is the first study on the quality of laparoscopic hysterectomy videos available on YouTube and the first study to evaluate YouTube laparoscopic surgery videos using the LAP-VEGaS Video Assessment Tool (VAT). Our study revealed the low educational quality of YouTube laparoscopic hysterectomy videos. The LAP-VEGaS VAT seems to be a valid and practical tool for assessing online laparoscopic hysterectomy videos.What are the implications of these findings for clinical practice and/or further research? Medical communities, especially tertiary care or academic centres, may upload educational peer-reviewed videos for trainees seeking this type of resource, especially during the coronavirus disease pandemic, as surgical education alternatives are limited.