Enhancing textbook study experiences with pictorial bar-codes and augmented reality

5Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Augmented Reality (AR) could overlay computer-generated graphics onto the student’s textbooks to make them more attractive, hence, motivate students to learn. However, most existing AR applications use either template (picture) markers or bar-code markers to conceal the information that it wants to display. The formal, being in a pictorial form, can be recognized easily but they are computationally expensive to generate and cannot be easily decoded. The latter displays only numeric data and are therefore cheap to produce and straightforward to decode. However, they look uninteresting and uninformative. In this paper, we present a way that combines the advantage of both the template and bar-code markers to be used in education, e.g. textbook’s figures. Our method decorates on top of an original pictorial textbook’s figure (e.g. historical photos, images, graphs, charts, maps, or drawings) additional regions, to form a single image stereogram that conceals a bar-code. This novel type of figure displays not only a realistic-looking picture but also contains encoded numeric information on students’ textbooks. Students can turn the pages of the book, look at the figures, and understand them without any additional technology. However, if students observe the pages through a hand-held Augmented Reality devices, they see 3D virtual models appearing out of the pages. In this article, we also demonstrate that this pictorial bar-code is relatively robust under various conditions and scaling. Thus, it provides a promising AR approach to be used in school textbooks of all grades, to enhance study experiences.

Cite

CITATION STYLE

APA

Le, H., & Nguyen, M. (2017). Enhancing textbook study experiences with pictorial bar-codes and augmented reality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10425 LNCS, pp. 139–150). Springer Verlag. https://doi.org/10.1007/978-3-319-64698-5_13

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free