{"title":"Towards an efficient methodology for evaluation of quality of experience in Augmented Reality","authors":"Jordi Puig, A. Perkis, F. Lindseth, T. Ebrahimi","doi":"10.1109/QoMEX.2012.6263864","DOIUrl":null,"url":null,"abstract":"The goal of this paper is to survey existing quality assessment methodologies for Augmented Reality (AR) visualization and to introduce a methodology for subjective quality assessment. Methodologies to assess the quality of AR systems have existed since these technologies appeared. The existing methodologies typically take an approach from the fields they are used in, such as ergonomics, usability, psychophysics or ethnography. Each field utilizes different methods, looking at different aspects of AR quality such as physical limitations, tracking loss or jitter, perceptual issues or feedback issues, just to name a few. AR systems are complex experiences, involving a mix of user interaction, visual perception, audio, haptic or other types of multimodal interactions as well. This paper focuses on the quality assessment of AR visualization, with a special interest on applications for neuronavigation.","PeriodicalId":6303,"journal":{"name":"2012 Fourth International Workshop on Quality of Multimedia Experience","volume":"25 1","pages":"188-193"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fourth International Workshop on Quality of Multimedia Experience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QoMEX.2012.6263864","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
The goal of this paper is to survey existing quality assessment methodologies for Augmented Reality (AR) visualization and to introduce a methodology for subjective quality assessment. Methodologies to assess the quality of AR systems have existed since these technologies appeared. The existing methodologies typically take an approach from the fields they are used in, such as ergonomics, usability, psychophysics or ethnography. Each field utilizes different methods, looking at different aspects of AR quality such as physical limitations, tracking loss or jitter, perceptual issues or feedback issues, just to name a few. AR systems are complex experiences, involving a mix of user interaction, visual perception, audio, haptic or other types of multimodal interactions as well. This paper focuses on the quality assessment of AR visualization, with a special interest on applications for neuronavigation.