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http://dx.doi.org/10.22156/CS4SMB.2021.11.11.038

A Study on the Analysis of Background Object Using Deep Learning in Augmented Reality Game  

Kim, Han-Ho (Dept. of Game Design, Kongju University)
Lee, Dong-Lyeor (Dept. of Game Design, Kongju University)
Publication Information
Journal of Convergence for Information Technology / v.11, no.11, 2021 , pp. 38-43 More about this Journal
Abstract
As the number of augmented reality games using augmented reality technology increases, the demands of users are also increasing. Game technologies used in augmented reality games are mainly games using MARKER, MARKERLESS, GPS, etc. Games using this technology can augment the background and other objects. To solve this problem, we want to help develop augmented reality games by analyzing objects in the background, which is an important element of augmented reality. To analyze the background in the augmented reality game, the background object was analyzed by applying a deep learning model using TensorFlow Lite in the UNITY engine. Using this result, we obtained the result that augmented objects can be placed in the game according to the types of objects analyzed in the background. By utilizing this research, it will be possible to develop advanced augmented reality games by augmenting objects that fit the background.
Keywords
AR; DeepLearning; Tensorflow Lite; AR background; AR game; Oobject detection;
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Times Cited By KSCI : 1  (Citation Analysis)
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