Development of AR Information System Based on Deep Learning and Gamification

Book Chapter (2018)
Author(s)

Tetsuro Ogi (Keio University Yokohama)

Yusuke Takesue (Keio University Yokohama)

Stephan Lukosch (TU Delft - Technology, Policy and Management)

Research Group
System Engineering
DOI related publication
https://doi.org/10.1007/978-3-319-98530-5_41 Final published version
More Info
expand_more
Publication Year
2018
Language
English
Research Group
System Engineering
Pages (from-to)
485-493
Publisher
Springer
ISBN (print)
978-3-319-98529-9
ISBN (electronic)
978-3-319-98530-5
Event
International Conference on Network-Based Information Systems (NBiS 2018) (2018-09-05 - 2018-09-07), Bratislava, Slovakia
Downloads counter
64

Abstract

Recently, several AR systems have been developed and used in various fields. However, in most AR systems, there are some restrictions caused by the usage of AR marker or location information. In this research, in order to solve these problems, AR information system that can recognize object itself based on deep learning was developed. In particular, this system was constructed using client-server model so that the machine learning can be updated while operating the system. In addition, the method of gamification was introduced to gather the learning data automatically from the users when they use the system. The prototype was applied to the AR zoo information system and the effectiveness of the proposed system was validated in the evaluation experiment.