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InfraredTags: Embedding Invisible AR Markers and Barcodes Using Low-Cost, Infrared-Based 3D Printing and Imaging Tools

Authors :
Dogan, Mustafa Doga
Taka, Ahmad
Lu, Michael
Zhu, Yunyi
Kumar, Akshat
Gupta, Aakar
Mueller, Stefanie
Publication Year :
2022

Abstract

Existing approaches for embedding unobtrusive tags inside 3D objects require either complex fabrication or high-cost imaging equipment. We present InfraredTags, which are 2D markers and barcodes imperceptible to the naked eye that can be 3D printed as part of objects, and detected rapidly by low-cost near-infrared cameras. We achieve this by printing objects from an infrared-transmitting filament, which infrared cameras can see through, and by having air gaps inside for the tag's bits, which appear at a different intensity in the infrared image. We built a user interface that facilitates the integration of common tags (QR codes, ArUco markers) with the object geometry to make them 3D printable as InfraredTags. We also developed a low-cost infrared imaging module that augments existing mobile devices and decodes tags using our image processing pipeline. Our evaluation shows that the tags can be detected with little near-infrared illumination (0.2lux) and from distances as far as 250cm. We demonstrate how our method enables various applications, such as object tracking and embedding metadata for augmented reality and tangible interactions.<br />Comment: 12 pages, 10 figures. To appear in the Proceedings of the 2022 ACM Conference on Human Factors in Computing Systems

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2202.06165
Document Type :
Working Paper
Full Text :
https://doi.org/10.1145/3491102.3501951