Abstract
In this paper, we introduce a new Augmented Reality (AR) Tag to enhance detection rates, accuracy and also user experiences in marker-based AR technologies. The tag is a colour printed card, divided into three colour channels: red, blue, and green; to label the three components: (1) an oriented marker, (2) a bar-code and (3) a graphic image, respectively. In this tag, the oriented marker is used for tag detection and orientation identification, the bar-code is for storing and achieving numerical information (IDs of the models), and the texture image is to provide the users with an original sight of what the tag is displaying. When our new AR tags are placed in front of the camera, the corresponding 3D graphics (models of figures or products) will appear directly on top of it. Also, we can rotate the tags to rotate the 3D graphics; and move the camera to zoom in/out or view it from a different angle. The embedded bar-code could be 1D or 2D bar-codes; the currently popular QR code could be used. Fortunately, QR codes include position detection patterns that could be used to identify the orientation for the code. Thus, the oriented marker is not needed for QR code, and one channel is saved and used for presenting the initially displaying image. Some experiments have been carried out to identify the robustness of the proposed tags. The results show that our tags and its orientations (marker stored in the blue colour channel) are relatively easy to detect using commodity webcams. The embedded QR code (painted in blue) is readable in most test cases. Compared to the ordinary QR tag (black and white), our embedded QR code has the detection rates of 95%. The image texture is stored in the red and green channel is relatively visible. However, the blue channel is missing, which makes it not visually correctly in some cases. Application-wise, this could be used in many AR applications such as shopping. Thanks to the large storage of QR Code, this AR Tag is capable of storing and displaying virtual products of a much wider variety. The user could see its 3D figure, zoom and rotate using intuitive on-hand controls.
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Nguyen, M., Le, H., Yan, W.Q. (2020). Red-Green-Blue Augmented Reality Tags for Retail Stores. In: Blanc-Talon, J., Delmas, P., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2020. Lecture Notes in Computer Science(), vol 12002. Springer, Cham. https://doi.org/10.1007/978-3-030-40605-9_40
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DOI: https://doi.org/10.1007/978-3-030-40605-9_40
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