2021 13th International Conference on Quality of Multimedia Experience (QoMEX)最新文献

How does it feel? - Investigating Soft-Touch Surface Experience Dimensions 感觉如何?-调查软触表面体验维度

2021 13th International Conference on Quality of Multimedia Experience (QoMEX) Pub Date : 2021-06-14 DOI: 10.1109/QoMEX51781.2021.9526677

Georg Regal, Sebastian Egger-Lampl, Till Bieg, Thomas Ules, M. Tscheligi, D. Gruber

引用次数: 0

The Effect of VR Gaming on Discomfort, Cybersickness, and Reaction Time VR游戏对不适、晕机和反应时间的影响

2021 13th International Conference on Quality of Multimedia Experience (QoMEX) Pub Date : 2021-06-14 DOI: 10.1109/QoMEX51781.2021.9465470

Sara Vlahovic, M. Sužnjević, Nina Pavlin-Bernardić, Lea Skorin-Kapov

{"title":"The Effect of VR Gaming on Discomfort, Cybersickness, and Reaction Time","authors":"Sara Vlahovic, M. Sužnjević, Nina Pavlin-Bernardić, Lea Skorin-Kapov","doi":"10.1109/QoMEX51781.2021.9465470","DOIUrl":"https://doi.org/10.1109/QoMEX51781.2021.9465470","url":null,"abstract":"The capabilities of commercial virtual reality (VR) systems can be utilized to implement a wide spectrum of interaction and locomotion methods. However, immersion in VR is often accompanied by undesirable physical sensations that undermine the VR gaming experience. Presenting the results of a user study (N=20) comparing the physiological and cognitive aftereffects of three different VR games with game mechanics centered around natural interaction, this paper attempts to shed light on the impact of different content factors (e.g., game genre, visual environment, interaction method) on user comfort. While moving away from cybersickness as the primary measure of VR-induced discomfort through investigating a broader set of physical symptoms, such as device-related discomfort, muscle fatigue, and pain, we also include a discussion on the complexities of measuring cybersickness for physically demanding games. Further focusing on cognitive performance, we discuss preliminary findings regarding different effects of common VR game interactions (pick and place, slicing, and shooting) on reaction time.","PeriodicalId":160378,"journal":{"name":"2021 13th International Conference on Quality of Multimedia Experience (QoMEX)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117177695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

The WEIRDness of QoE research: The diversity of QoMEX authorship considering locality and gender QoE研究的奇异性:考虑地域和性别的QoMEX作者多样性

2021 13th International Conference on Quality of Multimedia Experience (QoMEX) Pub Date : 2021-06-14 DOI: 10.1109/QoMEX51781.2021.9465413

Julia Himmelsbach, K. Moor, A. Sackl, R. Schatz, M. Tscheligi

引用次数: 0

Study on user quitting in the Puffer live TV video streaming service Puffer电视直播流媒体服务中用户退出问题研究

2021 13th International Conference on Quality of Multimedia Experience (QoMEX) Pub Date : 2021-06-14 DOI: 10.1109/QoMEX51781.2021.9465394

Pierre R. Lebreton, Kazuhisa Yamagishi

{"title":"Study on user quitting in the Puffer live TV video streaming service","authors":"Pierre R. Lebreton, Kazuhisa Yamagishi","doi":"10.1109/QoMEX51781.2021.9465394","DOIUrl":"https://doi.org/10.1109/QoMEX51781.2021.9465394","url":null,"abstract":"Video streaming is an important application on the Internet. To ensure user satisfaction, video streaming service providers monitor their services in terms of quality and engagement. This enables them to ensure high quality services and grow their platform and incomes. However, studying user engagement is difficult as the decision of a user to quit or continue watching videos is jointly affected by many factors such as interest towards content, time available, and service quality. Therefore, the reason for quitting is difficult to identify. To address this, this study is based on usage data of a real-world TV service called Puffer and aims to study the relationship between service quality and quitting actions. Data from December 2020 were collected and correspond to 230,880 distinct viewing sessions. On the basis of these data, performing analysis at different scales (hour, day, month) enables the identification of different reasons for users to quit videos. By using this analysis, quality-related quitting events are identified and put into relation with quality-related parameters as well as state-of-the-art video quality and user quitting prediction models. Results show that quitting prediction models can be used to identify such events. Finally, by the means of logistic regression, this work describes the first steps towards mapping quitting prediction on the basis of models trained using data from laboratory experiments to real-world scenarios and shows a classification accuracy of 75.9%.","PeriodicalId":160378,"journal":{"name":"2021 13th International Conference on Quality of Multimedia Experience (QoMEX)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123579462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Visualizing navigation difficulties in video game experiences 可视化电子游戏体验中的导航困难

2021 13th International Conference on Quality of Multimedia Experience (QoMEX) Pub Date : 2021-06-14 DOI: 10.1109/QoMEX51781.2021.9465423

Hippolyte Dubois, P. Callet, A. Coutrot

引用次数: 3

Full-Reference and No-Reference Objective Evaluation of Deep Neural Network Speech 深度神经网络语音的全参考和无参考客观评价

2021 13th International Conference on Quality of Multimedia Experience (QoMEX) Pub Date : 2021-06-14 DOI: 10.1109/QoMEX51781.2021.9465433

S. Voran

{"title":"Full-Reference and No-Reference Objective Evaluation of Deep Neural Network Speech","authors":"S. Voran","doi":"10.1109/QoMEX51781.2021.9465433","DOIUrl":"https://doi.org/10.1109/QoMEX51781.2021.9465433","url":null,"abstract":"Objective speech quality and intelligibility estimators do not correctly assess speech generated by deep neural networks (DNNs). We use 256 speech files and subjective scores that cover 14 DNN speech conditions and 18 nonDNN speech conditions to show that 8 different full-reference (FR) estimators consistently underestimate subjective scores for the DNN conditions. Conversely, we find that five no-reference (NR) estimators consistently overestimate subjective scores for the DNN conditions. We show that a rudimentary but effective solution to these shortcomings is to simply average an FR result with an NR result. We also explore root causes and propose more fundamental solutions. It has been previously suggested that FR estimators over-penalize inaudible timing variations or jitter. We conduct several experiments that measure and remove jitter from spectral representations of DNN speech inside FR estimators. Jitter removal compensates for some of the underestimation, thus confirming that jitter is a part of the cause. In additional experiments we show that power mismatches on a syllabic time-scale also contribute to the underestimation issue in FR estimators. Regarding NR estimators, we suggest that they can be trained to accurately rate DNN speech when sufficient speech signals and corresponding subjective scores are available.","PeriodicalId":160378,"journal":{"name":"2021 13th International Conference on Quality of Multimedia Experience (QoMEX)","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115996350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Evaluating Hand-tracking Interaction for Performing Motor-tasks in VR Learning Environments 评估在VR学习环境中执行运动任务的手跟踪交互

2021 13th International Conference on Quality of Multimedia Experience (QoMEX) Pub Date : 2021-06-14 DOI: 10.1109/QoMEX51781.2021.9465407

Asim Hameed, A. Perkis, Sebastian Möller

{"title":"Evaluating Hand-tracking Interaction for Performing Motor-tasks in VR Learning Environments","authors":"Asim Hameed, A. Perkis, Sebastian Möller","doi":"10.1109/QoMEX51781.2021.9465407","DOIUrl":"https://doi.org/10.1109/QoMEX51781.2021.9465407","url":null,"abstract":"The past few years has witnessed a promising surge in immersive media technologies, however, a widespread adoption is still some years away. Recently, virtual reality (VR) head-mounted displays with inside-out tracking and hand-tracking are becoming popular in various fields. Representing users’ hands and fingers in VR is crucial for many tasks. This is because hand-tracking enables a more natural, direct, interaction with a virtual environment (VE) which, compared to traditional handheld controllers, improves the VR immersive experience. This paper investigates user-perceived quality of experience for a reach-pick-place task inside VR. It presents a performance assessment methodology based on in-game analytics to evaluate user experience for different VR interaction types. We ran a controlled experiment (N=33) comparing two commodities: controller vs. hand-tracking. Results indicate a significant difference between the two data sets. The performance analytics show lower play-durations and trigger frequencies for the handheld controller compared to hand-tracking. The perceived mental workload for the tasks was also evaluated using Rated Scale Mental Effort (RSME). The reported scores were higher when using hand-tracking. The results help our understanding of the two interaction modalities in terms of their viability for naturalistic experiences akin to real-world scenarios.","PeriodicalId":160378,"journal":{"name":"2021 13th International Conference on Quality of Multimedia Experience (QoMEX)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128256887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

More for Less: Non-Intrusive Speech Quality Assessment with Limited Annotations 少花钱多:有限注释的非侵入性语音质量评估

2021 13th International Conference on Quality of Multimedia Experience (QoMEX) Pub Date : 2021-06-14 DOI: 10.1109/QoMEX51781.2021.9465410

Alessandro Ragano, Emmanouil Benetos, Andrew Hines

{"title":"More for Less: Non-Intrusive Speech Quality Assessment with Limited Annotations","authors":"Alessandro Ragano, Emmanouil Benetos, Andrew Hines","doi":"10.1109/QoMEX51781.2021.9465410","DOIUrl":"https://doi.org/10.1109/QoMEX51781.2021.9465410","url":null,"abstract":"Non-intrusive speech quality assessment is a crucial operation in multimedia applications. The scarcity of annotated data and the lack of a reference signal represent some of the main challenges for designing efficient quality assessment metrics. In this paper, we propose two multi-task models to tackle the problems above. In the first model, we first learn a feature representation with a degradation classifier on a large dataset. Then we perform MOS prediction and degradation classification simultaneously on a small dataset annotated with MOS. In the second approach, the initial stage consists of learning features with a deep clustering-based unsupervised feature representation on the large dataset. Next, we perform MOS prediction and cluster label classification simultaneously on a small dataset. The results show that the deep clustering-based model outperforms the degradation classifier-based model and the 3 baselines (autoencoder features, P.563, and SRMRnorm) on TCD-VoIP. This paper indicates that multi-task learning combined with feature representations from unlabelled data is a promising approach to deal with the lack of large MOS annotated datasets.","PeriodicalId":160378,"journal":{"name":"2021 13th International Conference on Quality of Multimedia Experience (QoMEX)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122911118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

QoE Models in the Wild: Comparing Video QoE Models Using a Crowdsourced Data Set 野外QoE模型:使用众包数据集比较视频QoE模型

2021 13th International Conference on Quality of Multimedia Experience (QoMEX) Pub Date : 2021-06-14 DOI: 10.1109/QoMEX51781.2021.9465422

Anna-Magdalena Seufert, Florian Wamser, D. Yarish, Hunter Macdonald, T. Hossfeld

{"title":"QoE Models in the Wild: Comparing Video QoE Models Using a Crowdsourced Data Set","authors":"Anna-Magdalena Seufert, Florian Wamser, D. Yarish, Hunter Macdonald, T. Hossfeld","doi":"10.1109/QoMEX51781.2021.9465422","DOIUrl":"https://doi.org/10.1109/QoMEX51781.2021.9465422","url":null,"abstract":"Crowdsourced measurements solve the problem of being able to assess the performance of a communication network from an end-user perspective, but the new characteristics of the data pose new challenges for QoE modeling. In contrast to existing laboratory or network measurements, this type of measurement at the end user device primarily involves taking a large number of short sample measurements, which, however, are rich in measured parameters, including many user-, application-, and device-related parameters. To test the applicability and to facilitate the integration of such data, we applied four QoE models from the literature to 290k worldwide video streaming measurements from a commercial data set from August to October 2020. In this work, we will therefore first describe the crowdsourcing video streaming data set to provide insights into the properties of video streaming KPIs in the real world. Second, we run four popular QoE models using this data set, compare the resulting QoE scores, and derive the impact of individual KPIs for each model. We show that the models assess the QoE at least differently, but sometimes with contradicting statements. Reading this paper, it becomes evident that more work and subjective studies, based on real-world data like the one we have shown, are needed to extend the current QoE models.","PeriodicalId":160378,"journal":{"name":"2021 13th International Conference on Quality of Multimedia Experience (QoMEX)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115363541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Modeling and Understanding the Quality of Experience of Online Mobile Gaming Services 建模和理解在线手机游戏服务的体验质量

2021 13th International Conference on Quality of Multimedia Experience (QoMEX) Pub Date : 2021-06-14 DOI: 10.1109/QoMEX51781.2021.9465431

Steven Schmidt, Saman Zadtootaghaj, S. Sabet, S. Möller

引用次数: 7