Abstract
In this paper, we present a user-adaptive augmented reality (AR) system that augments physical objects with personalized content according to user’s context as well as preferences. Since a user prefers different content according to the context, it reasons the user’s recent content preferences through artificial neural networks trained with the feedback history describing which content the user liked or disliked with respect to his/her context. The system recommends a set of content relevant to the user’s context and preferences. Then, it enables the user to select a preferred content among the recommended set and superimposes the selected content over physical objects.We implemented a prototype illustrating how our system could be used in daily life and evaluate its performance. From experimental results, we could confirm that our system effectively assisted users through personalized content augmentation in mobile computing environment.
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Oh, S., Byun, YC. (2012). A User-Adaptive Augmented Reality System in Mobile Computing Environment. In: Lee, R. (eds) Software and Network Engineering. Studies in Computational Intelligence, vol 413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28670-4_4
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DOI: https://doi.org/10.1007/978-3-642-28670-4_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28669-8
Online ISBN: 978-3-642-28670-4
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