Unterschiede
Hier werden die Unterschiede zwischen zwei Versionen angezeigt.
| Beide Seiten der vorigen RevisionVorhergehende Überarbeitung | |
| lehre:ws18:fsm_18ws:group_g [26.03.2019 10:53] – scc64279 | lehre:ws18:fsm_18ws:group_g [26.03.2019 10:54] (aktuell) – scc64279 |
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| members_ : Marlena Wolfes, Christine Schikora, Sümeyye Reyyan Yildiran | members_ : Marlena Wolfes, Christine Schikora, Sümeyye Reyyan Yildiran |
| keywords_ : WIP, AR, user study, augmented reality | keywords_ : WIP, AR, user study, augmented reality |
| photo_img : {{:lehre:ws18:fsm_18ws:tempsnip.png?400|}} | photo_img : {{:lehre:ws18:fsm_18ws:tempsnip.png?700|}} |
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| shortdescription : The emergence of Augmented Reality (AR) in the last decades was characterized by a shift from exclusively industrial and governmental to commercial accessibility. This includes an expansion and advancement of the underlying technologies and therefore an increasing complexity and loss of overview of available methods. For this reason, it is difficult for developers to find suitable technologies and methods for evaluating AR applications that offer high validity and reliability. To overcome this issue, a taxonomy could provide an overview over all available possibilities as well as illustrate the linkage between single elements within a larger hierarchy. However, in the literature few classifications of AR technologies and evaluation methods can be found. In our paper we propose taxonomies of AR technologies and evaluation methods and show their applicability, generalizability and expandability by analyzing state-of-the-art AR publications and the used technologies and evaluation methods. By applying different selection criteria we reduced the corpus of publications from 405 to 135 covering the years 2015 to 2017.We analyzed usage frequencies and drew comparisons to results from the literature as well as identified limitations, problems and trends in current AR research. The most preferred technologies in our analysis are represented by visual displays with head-mounted or handheld positionings, optical tracking sensors as well as touch and body motion as input types. Regarding evaluation-related results, user performance and system technology as well as task-based application tests were the most preferred evaluation areas and methods. | shortdescription : The emergence of Augmented Reality (AR) in the last decades was characterized by a shift from exclusively industrial and governmental to commercial accessibility. This includes an expansion and advancement of the underlying technologies and therefore an increasing complexity and loss of overview of available methods. For this reason, it is difficult for developers to find suitable technologies and methods for evaluating AR applications that offer high validity and reliability. To overcome this issue, a taxonomy could provide an overview over all available possibilities as well as illustrate the linkage between single elements within a larger hierarchy. However, in the literature few classifications of AR technologies and evaluation methods can be found. In our paper we propose taxonomies of AR technologies and evaluation methods and show their applicability, generalizability and expandability by analyzing state-of-the-art AR publications and the used technologies and evaluation methods. By applying different selection criteria we reduced the corpus of publications from 405 to 135 covering the years 2015 to 2017.We analyzed usage frequencies and drew comparisons to results from the literature as well as identified limitations, problems and trends in current AR research. The most preferred technologies in our analysis are represented by visual displays with head-mounted or handheld positionings, optical tracking sensors as well as touch and body motion as input types. Regarding evaluation-related results, user performance and system technology as well as task-based application tests were the most preferred evaluation areas and methods. |