Pub Date : 2018-09-13DOI: 10.1109/QoMEX.2018.8463408
M. Narbutt, Andrew Allen, J. Skoglund, Michael Chinen, Andrew Hines
Streaming spatial audio over networks requires efficient encoding techniques that compress the raw audio content without compromising quality of experience. Streaming service providers such as YouTube need a perceptually relevant objective audio quality metric to monitor users' perceived quality and spatial localization accuracy. In this paper we introduce a full reference objective spatial audio quality metric, AMBIQUAL, which assesses both Listening Quality and Localization Accuracy. In our solution both metrics are derived directly from the B-format Ambisonic audio. The metric extends and adapts the algorithm used in ViSQOLAudio, a full reference objective metric designed for assessing speech and audio quality. In particular, Listening Quality is derived from the omnidirectional channel and Localization Accuracy is derived from a weighted sum of similarity from B-format directional channels. This paper evaluates whether the proposed AMBIQUAL objective spatial audio quality metric can predict two factors: Listening Quality and Localization Accuracy by comparing its predictions with results from MUSHRA subjective listening tests. In particular, we evaluated the Listening Quality and Localization Accuracy of First and Third-Order Ambisonic audio compressed with the OPUS 1.2 codec at various bitrates (i.e. 32, 128 and 256, 512kbps respectively). The sample set for the tests comprised both recorded and synthetic audio clips with a wide range of time-frequency characteristics. To evaluate Localization Accuracy of compressed audio a number of fixed and dynamic (moving vertically and horizontally) source positions were selected for the test samples. Results showed a strong correlation (PCC=0.919; Spearman=0.882 regarding Listening Quality and PCC=0.854; Spearman=0.842 regarding Localization Accuracy) between objective quality scores derived from the B-format Ambisonic audio using AMBIQUAL and subjective scores obtained during listening MUSHRA tests. AMBIQUAL displays very promising quality assessment predictions for spatial audio. Future work will optimise the algorithm to generalise and validate it for any Higher Order Ambisonic formats.
{"title":"AMBIQUAL - a full reference objective quality metric for ambisonic spatial audio","authors":"M. Narbutt, Andrew Allen, J. Skoglund, Michael Chinen, Andrew Hines","doi":"10.1109/QoMEX.2018.8463408","DOIUrl":"https://doi.org/10.1109/QoMEX.2018.8463408","url":null,"abstract":"Streaming spatial audio over networks requires efficient encoding techniques that compress the raw audio content without compromising quality of experience. Streaming service providers such as YouTube need a perceptually relevant objective audio quality metric to monitor users' perceived quality and spatial localization accuracy. In this paper we introduce a full reference objective spatial audio quality metric, AMBIQUAL, which assesses both Listening Quality and Localization Accuracy. In our solution both metrics are derived directly from the B-format Ambisonic audio. The metric extends and adapts the algorithm used in ViSQOLAudio, a full reference objective metric designed for assessing speech and audio quality. In particular, Listening Quality is derived from the omnidirectional channel and Localization Accuracy is derived from a weighted sum of similarity from B-format directional channels. This paper evaluates whether the proposed AMBIQUAL objective spatial audio quality metric can predict two factors: Listening Quality and Localization Accuracy by comparing its predictions with results from MUSHRA subjective listening tests. In particular, we evaluated the Listening Quality and Localization Accuracy of First and Third-Order Ambisonic audio compressed with the OPUS 1.2 codec at various bitrates (i.e. 32, 128 and 256, 512kbps respectively). The sample set for the tests comprised both recorded and synthetic audio clips with a wide range of time-frequency characteristics. To evaluate Localization Accuracy of compressed audio a number of fixed and dynamic (moving vertically and horizontally) source positions were selected for the test samples. Results showed a strong correlation (PCC=0.919; Spearman=0.882 regarding Listening Quality and PCC=0.854; Spearman=0.842 regarding Localization Accuracy) between objective quality scores derived from the B-format Ambisonic audio using AMBIQUAL and subjective scores obtained during listening MUSHRA tests. AMBIQUAL displays very promising quality assessment predictions for spatial audio. Future work will optimise the algorithm to generalise and validate it for any Higher Order Ambisonic formats.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"146 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78135052","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}
Pub Date : 2018-09-11DOI: 10.1109/QoMEX.2018.8463389
Steven Schmidt, Patrick Ehrenbrink, Benjamin Weiss, Jan-Niklas Voigt-Antons, Tanja Kojić, Andrew Johnston, S. Möller
Video games and sport are an essential part in the life of millions of people. With recent advances of immersive virtual reality devices such as the HTC Vive, Oculus Rift, or PlayStation VR, the use of virtual environments (VE) for exergames is becoming more and more popular. An exergame combines a physical activity with video game elements by tracking body movements or reactions of user, attempting to engage users in a more enjoyable system. In this paper, we present the results of a subjective experiment carried out with the aim to compare different kinds of virtual environments with each other. A rowing ergometer, connected either to a virtual reality system using a head-mounted display (HMD) or to a CAVE environment, was used as an exergame device. While for rowing experts, fitness and performance improvements are of major interest, we wanted to focus on the motivation and engagement of non-professionals. By means of a series of questionnaires and a follow-up interview, the Quality of Experience of participants using the system was assessed. Measurements include concepts such as flow, presence, video quality and well-being. Results show significant advantages of the HMD as well as of the CAVE compared to a system without a VE for the overall quality, system feedback, and flow. While the CAVE and HMD system mainly differed in their autotelic experience, the HMD was favored by the majority of participants due to a superior feeling of presence.
{"title":"Impact of Virtual Environments on Motivation and Engagement During Exergames","authors":"Steven Schmidt, Patrick Ehrenbrink, Benjamin Weiss, Jan-Niklas Voigt-Antons, Tanja Kojić, Andrew Johnston, S. Möller","doi":"10.1109/QoMEX.2018.8463389","DOIUrl":"https://doi.org/10.1109/QoMEX.2018.8463389","url":null,"abstract":"Video games and sport are an essential part in the life of millions of people. With recent advances of immersive virtual reality devices such as the HTC Vive, Oculus Rift, or PlayStation VR, the use of virtual environments (VE) for exergames is becoming more and more popular. An exergame combines a physical activity with video game elements by tracking body movements or reactions of user, attempting to engage users in a more enjoyable system. In this paper, we present the results of a subjective experiment carried out with the aim to compare different kinds of virtual environments with each other. A rowing ergometer, connected either to a virtual reality system using a head-mounted display (HMD) or to a CAVE environment, was used as an exergame device. While for rowing experts, fitness and performance improvements are of major interest, we wanted to focus on the motivation and engagement of non-professionals. By means of a series of questionnaires and a follow-up interview, the Quality of Experience of participants using the system was assessed. Measurements include concepts such as flow, presence, video quality and well-being. Results show significant advantages of the HMD as well as of the CAVE compared to a system without a VE for the overall quality, system feedback, and flow. While the CAVE and HMD system mainly differed in their autotelic experience, the HMD was favored by the majority of participants due to a superior feeling of presence.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"34 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81449875","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}
Pub Date : 2018-09-11DOI: 10.1109/QoMEX.2018.8463403
Nabajeet Barman, M. Martini, Saman Zadtootaghaj, S. Möller, Sanghoon Lee
Recent years have seen a tremendous increase in video traffic with the rise of Over The Top (OTT) services. Along with traditional Video on demand (VoD) streaming services (e.g., Netflix, YouTube), live video services (e.g., Twitch. tv, YouTubeGaming, Facebook Live) have also resulted in a tremendous share of Internet traffic. Among the live streaming services, gaming video streaming has a major share, with Twitch.tv alone currently responsible for the fourth highest peak Internet traffic in the US. As a consequence of this, and due to the fact that gaming videos are artificial and synthetic, it is worth investigating the specificity of gaming videos in relation to compression and the consequent end user QoE. In this paper, we present an objective and subjective quality comparison study for regular videos and gaming videos, with 30 video sequences (15 per type), encoded using the state of the art encoder HEVC. We discuss the similarity and dissimilarity between the two video types and also discuss how these observations can be used to improve the end user QoE.
近年来，随着OTT (Over the Top)服务的兴起，视频流量大幅增加。除了传统的视频点播(VoD)流媒体服务(如Netflix, YouTube)，直播视频服务(如Twitch)。tv, youtubeaming, Facebook Live)也带来了巨大的互联网流量份额。在直播服务中，游戏视频流占有很大的份额，比如Twitch。目前，仅电视就负责美国第四高峰的互联网流量。因此，由于游戏视频是人工合成的，我们有必要研究一下游戏视频在压缩和最终用户QoE方面的特殊性。在本文中，我们对常规视频和游戏视频进行了客观和主观的质量比较研究，其中30个视频序列(每种类型15个)使用最先进的编码器HEVC进行编码。我们讨论了这两种视频类型之间的相似性和差异性，并讨论了如何使用这些观察结果来改善最终用户的QoE。
{"title":"A Comparative Quality Assessment Study for Gaming and Non-Gaming Videos","authors":"Nabajeet Barman, M. Martini, Saman Zadtootaghaj, S. Möller, Sanghoon Lee","doi":"10.1109/QoMEX.2018.8463403","DOIUrl":"https://doi.org/10.1109/QoMEX.2018.8463403","url":null,"abstract":"Recent years have seen a tremendous increase in video traffic with the rise of Over The Top (OTT) services. Along with traditional Video on demand (VoD) streaming services (e.g., Netflix, YouTube), live video services (e.g., Twitch. tv, YouTubeGaming, Facebook Live) have also resulted in a tremendous share of Internet traffic. Among the live streaming services, gaming video streaming has a major share, with Twitch.tv alone currently responsible for the fourth highest peak Internet traffic in the US. As a consequence of this, and due to the fact that gaming videos are artificial and synthetic, it is worth investigating the specificity of gaming videos in relation to compression and the consequent end user QoE. In this paper, we present an objective and subjective quality comparison study for regular videos and gaming videos, with 30 video sequences (15 per type), encoded using the state of the art encoder HEVC. We discuss the similarity and dissimilarity between the two video types and also discuss how these observations can be used to improve the end user QoE.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"45 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90199539","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}
Pub Date : 2018-09-11DOI: 10.1109/QoMEX.2018.8463295
Anne Juhler Hansen, H. Knoche, T. Moeslund
The production of high-end manufactured products requires expensive human aesthetic quality control (AQC) in the form of e.g. visual inspection at multiple stages during production. Current standards for aesthetic quality control focus on the process, i.e. identifying the source of anomalies and lack an observer-oriented classification (describing the perceived appearance). We found a need for a perceptual categorization of anomalies that can help assessors making quality judgments and we present a judgment model for AQC. To this end, we studied visual inspection task flows, and processes especially around limit samples at Bang & Olufsen. Based on perceptual responses in the human visual system, we propose a categorization consisting of open and closed shapes. The latter contains areas, lines, alignment, and constellations. The categorization can help in automating AQC using computer vision.
{"title":"Getting Crevices, Cracks, and Grooves in Line: Anomaly Categorization for AQC Judgment Models","authors":"Anne Juhler Hansen, H. Knoche, T. Moeslund","doi":"10.1109/QoMEX.2018.8463295","DOIUrl":"https://doi.org/10.1109/QoMEX.2018.8463295","url":null,"abstract":"The production of high-end manufactured products requires expensive human aesthetic quality control (AQC) in the form of e.g. visual inspection at multiple stages during production. Current standards for aesthetic quality control focus on the process, i.e. identifying the source of anomalies and lack an observer-oriented classification (describing the perceived appearance). We found a need for a perceptual categorization of anomalies that can help assessors making quality judgments and we present a judgment model for AQC. To this end, we studied visual inspection task flows, and processes especially around limit samples at Bang & Olufsen. Based on perceptual responses in the human visual system, we propose a categorization consisting of open and closed shapes. The latter contains areas, lines, alignment, and constellations. The categorization can help in automating AQC using computer vision.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"15 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2018-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80293964","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}
Pub Date : 2018-09-11DOI: 10.1109/QoMEX.2018.8463373
Seong-eun Moon, Soobeom Jang, Jong-Seok Lee
Evaluation of quality of experience (Qo $E$) based on electroencephalography (EEG) has received great attention due to its capability of real-time Qo $E$ monitoring of users. However, it still suffers from rather low recognition accuracy. In this paper, we propose a novel method using deep neural networks toward improved modeling of EEG and thereby improved recognition accuracy. In particular, we aim to model spatio-temporal characteristics relevant for QoE analysis within learning models. The results demonstrate the effectiveness of the proposed method.
{"title":"Evaluation of preference of multimedia content using deep neural networks for electroencephalography","authors":"Seong-eun Moon, Soobeom Jang, Jong-Seok Lee","doi":"10.1109/QoMEX.2018.8463373","DOIUrl":"https://doi.org/10.1109/QoMEX.2018.8463373","url":null,"abstract":"Evaluation of quality of experience (Qo $E$) based on electroencephalography (EEG) has received great attention due to its capability of real-time Qo $E$ monitoring of users. However, it still suffers from rather low recognition accuracy. In this paper, we propose a novel method using deep neural networks toward improved modeling of EEG and thereby improved recognition accuracy. In particular, we aim to model spatio-temporal characteristics relevant for QoE analysis within learning models. The results demonstrate the effectiveness of the proposed method.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"2 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87447409","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}
Pub Date : 2018-06-03DOI: 10.1109/QoMEX.2018.8463406
E. Alexiou, T. Ebrahimi, Marco V. Bernardo, Manuela Pereira, A. Pinheiro, L. Cruz, C. Duarte, L. G. Dmitrovic, E. Dumic, Dragan Matkovics, A. Skodras
Point clouds are one of the most promising technologies for 3D content representation. In this paper, we describe a study on quality assessment of point clouds, degraded by octree-based compression on different levels. The test contents were displayed using Screened Poisson surface reconstruction, without including any textural information, and they were rated by subjects in a passive way, using a 2D image sequence. Subjective evaluations were performed in five independent laboratories in different countries, with the inter-laboratory correlation analysis showing no statistical differences, despite the different equipment employed. Benchmarking results reveal that the state-of-the-art point cloud objective metrics are not able to accurately predict the expected visual quality of such test contents. Moreover, the subjective scores collected from this experiment were found to be poorly correlated with subjective scores obtained from another test involving visualization of raw point clouds. These results suggest the need for further investigations on adequate point cloud representations and objective Quality assessment tools.
{"title":"Point Cloud Subjective Evaluation Methodology based on 2D Rendering","authors":"E. Alexiou, T. Ebrahimi, Marco V. Bernardo, Manuela Pereira, A. Pinheiro, L. Cruz, C. Duarte, L. G. Dmitrovic, E. Dumic, Dragan Matkovics, A. Skodras","doi":"10.1109/QoMEX.2018.8463406","DOIUrl":"https://doi.org/10.1109/QoMEX.2018.8463406","url":null,"abstract":"Point clouds are one of the most promising technologies for 3D content representation. In this paper, we describe a study on quality assessment of point clouds, degraded by octree-based compression on different levels. The test contents were displayed using Screened Poisson surface reconstruction, without including any textural information, and they were rated by subjects in a passive way, using a 2D image sequence. Subjective evaluations were performed in five independent laboratories in different countries, with the inter-laboratory correlation analysis showing no statistical differences, despite the different equipment employed. Benchmarking results reveal that the state-of-the-art point cloud objective metrics are not able to accurately predict the expected visual quality of such test contents. Moreover, the subjective scores collected from this experiment were found to be poorly correlated with subjective scores obtained from another test involving visualization of raw point clouds. These results suggest the need for further investigations on adequate point cloud representations and objective Quality assessment tools.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"70 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76204209","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}
Pub Date : 2018-05-29DOI: 10.1109/QoMEX.2018.8463297
Lucie Lévêque, Hantao Liu, Sabina Baraković, J. Barakovic, M. Martini, M. Outtas, Lu Zhang, A. Kumcu, L. Platisa, Rafael Rodrigues, António M. G. Pinheiro, A. Skodras
Medical professionals are viewing an increasing number of images and videos in their clinical routine. However, various types of distortions can affect medical imaging data, and therefore impact the viewers' experienced quality and their clinical practice. Thus it is necessary to quantify this impact and understand how the viewers, i.e., medical experts, perceive the quality of (distorted) images and videos. In this paper, we present an up-to-date review of the methodologies used in the literature for the subjective quality assessment of medical images and videos and discuss their merits and drawbacks depending on the use case.
{"title":"On the Subjective Assessment of the Perceived Quality of Medical Images and Videos","authors":"Lucie Lévêque, Hantao Liu, Sabina Baraković, J. Barakovic, M. Martini, M. Outtas, Lu Zhang, A. Kumcu, L. Platisa, Rafael Rodrigues, António M. G. Pinheiro, A. Skodras","doi":"10.1109/QoMEX.2018.8463297","DOIUrl":"https://doi.org/10.1109/QoMEX.2018.8463297","url":null,"abstract":"Medical professionals are viewing an increasing number of images and videos in their clinical routine. However, various types of distortions can affect medical imaging data, and therefore impact the viewers' experienced quality and their clinical practice. Thus it is necessary to quantify this impact and understand how the viewers, i.e., medical experts, perceive the quality of (distorted) images and videos. In this paper, we present an up-to-date review of the methodologies used in the literature for the subjective quality assessment of medical images and videos and discuss their merits and drawbacks depending on the use case.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"60 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78144343","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}
Pub Date : 2018-05-29DOI: 10.1109/QoMEX.2018.8463409
I. Comsa, R. Trestian, George Ghinea
The next generation of wireless networks targets aspiring key performance indicators, like very low latency, higher data rates and more capacity, paving the way for new generations of video streaming technologies, such as 360° or omnidirectional videos. One possible application that could revolutionize the streaming technology is the 360° MULtiple SEnsorial MEDIA (MULSEMEDIA) which enriches the 360° video content with other media objects like olfactory, haptic or even thermoceptic ones. However, the adoption of the 360° Mulsemedia applications might be hindered by the strict Quality of Service (QoS) requirements, like very large bandwidth and low latency for fast responsiveness to the user's inputs that could impact their Quality of Experience (QoE). To this extent, this paper introduces the new concept of 360° Mulsemedia as well as it proposes the use of Reinforcement Learning to enable QoS provisioning over the next generation wireless networks that influences the QoE of the end-users.
{"title":"360° Mulsemedia Experience over Next Generation Wireless Networks - A Reinforcement Learning Approach","authors":"I. Comsa, R. Trestian, George Ghinea","doi":"10.1109/QoMEX.2018.8463409","DOIUrl":"https://doi.org/10.1109/QoMEX.2018.8463409","url":null,"abstract":"The next generation of wireless networks targets aspiring key performance indicators, like very low latency, higher data rates and more capacity, paving the way for new generations of video streaming technologies, such as 360° or omnidirectional videos. One possible application that could revolutionize the streaming technology is the 360° MULtiple SEnsorial MEDIA (MULSEMEDIA) which enriches the 360° video content with other media objects like olfactory, haptic or even thermoceptic ones. However, the adoption of the 360° Mulsemedia applications might be hindered by the strict Quality of Service (QoS) requirements, like very large bandwidth and low latency for fast responsiveness to the user's inputs that could impact their Quality of Experience (QoE). To this extent, this paper introduces the new concept of 360° Mulsemedia as well as it proposes the use of Reinforcement Learning to enable QoS provisioning over the next generation wireless networks that influences the QoE of the end-users.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"75 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74181305","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}
Pub Date : 2018-05-29DOI: 10.1109/QoMEX.2018.8463299
M. Outtas, Lu Zhang, O. Déforges, W. Hamidouche, A. Serir
Although assessing post-processed medical images is still done by radiologists (rather than computers), numerous algorithms dedicated to medical image processing are developed without taking into consideration the expert's perceived quality scores. In order to evaluate these algorithms, we study in this paper four No-Reference(NR) quality assessment metrics in terms of correlation with perceived scores of experts. These scores were obtained through subjective tests conducted on ultrasound (US) livers images. Results show that one NR metric among the four evaluated performs the best for assessing the quality of US images. However, further study is needed for the development of more suitable NR metrics.
{"title":"Evaluation of No-reference quality metrics for Ultrasound liver images","authors":"M. Outtas, Lu Zhang, O. Déforges, W. Hamidouche, A. Serir","doi":"10.1109/QoMEX.2018.8463299","DOIUrl":"https://doi.org/10.1109/QoMEX.2018.8463299","url":null,"abstract":"Although assessing post-processed medical images is still done by radiologists (rather than computers), numerous algorithms dedicated to medical image processing are developed without taking into consideration the expert's perceived quality scores. In order to evaluate these algorithms, we study in this paper four No-Reference(NR) quality assessment metrics in terms of correlation with perceived scores of experts. These scores were obtained through subjective tests conducted on ultrasound (US) livers images. Results show that one NR metric among the four evaluated performs the best for assessing the quality of US images. However, further study is needed for the development of more suitable NR metrics.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"38 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2018-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85426150","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}
Pub Date : 2018-05-12DOI: 10.1109/QoMEX.2018.8463433
Sara Vlahovic, M. Sužnjević, Lea Skorin-Kapov
This paper presents the results of a subjective study aimed at assessing different locomotion (may also be referred to as navigation) techniques in virtual reality environments. We implemented a simple virtual environment in which participants were asked to assess the following four techniques using the HTC Vive platform: teleportation, controller movement, controller movement with tunneling vision, and human joystick. A total of 29 participants took part in the study and rated perceived level of immersion, physical discomfort, and overall Quality of Experience for all tested locomotion techniques. Moreover, participants indicated whether they needed a break after a specific test due to physical discomfort. The results indicate that teleportation yields overall highest QoE and lowest discomfort.
{"title":"Subjective Assessment of Different Locomotion Techniques in Virtual Reality Environments","authors":"Sara Vlahovic, M. Sužnjević, Lea Skorin-Kapov","doi":"10.1109/QoMEX.2018.8463433","DOIUrl":"https://doi.org/10.1109/QoMEX.2018.8463433","url":null,"abstract":"This paper presents the results of a subjective study aimed at assessing different locomotion (may also be referred to as navigation) techniques in virtual reality environments. We implemented a simple virtual environment in which participants were asked to assess the following four techniques using the HTC Vive platform: teleportation, controller movement, controller movement with tunneling vision, and human joystick. A total of 29 participants took part in the study and rated perceived level of immersion, physical discomfort, and overall Quality of Experience for all tested locomotion techniques. Moreover, participants indicated whether they needed a break after a specific test due to physical discomfort. The results indicate that teleportation yields overall highest QoE and lowest discomfort.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"99 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2018-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85782345","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}
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