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An Efficient Object Augmentation Scheme for Supporting Pervasiveness in a Mobile Augmented Reality

Authors
Jang, Sung-BongKo, Young-Woong
Issue Date
Oct-2020
Publisher
KOREA INFORMATION PROCESSING SOC
Keywords
Augmented Object Similarity; Context Awareness; Mobile Augmented Reality; Object Augmentation
Citation
JOURNAL OF INFORMATION PROCESSING SYSTEMS, v.16, no.5, pp.1214 - 1222
Journal Title
JOURNAL OF INFORMATION PROCESSING SYSTEMS
Volume
16
Number
5
Start Page
1214
End Page
1222
URI
https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/18508
DOI
10.3745/JIPS.04.0192
ISSN
1976-913X
Abstract
Pervasive augmented reality (AR) technology can be used to efficiently search for the required information regarding products in stores through text augmentation in an Internet of Things (IoT) environment. The evolution of context awareness and image processing technologies are the main driving forces that realize this type of AR service. One of the problems to be addressed in the service is that augmented objects are fixed and cannot be replaced efficiently in real time. To address this problem, a real-time mobile AR framework is proposed. In this framework, an optimal object to be augmented is selected based on object similarity comparison, and the augmented objects are efficiently managed using distributed metadata servers to adapt to the user requirements, in a given situation. To evaluate the feasibility of the proposed framework, a prototype system was implemented, and a qualitative evaluation based on questionnaires was conducted. The experimental results show that the proposed framework provides a better user experience than existing features in smartphones, and through fast AR service, the users are able to conveniently obtain additional information on products or objects.
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College of Engineering (Industry-Academic Co. Fund.)
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