English

AnisoTag: 3D Printed Tag on 2D Surface via Reflection Anisotropy

Human-Computer Interaction 2023-01-30 v2

Abstract

In the past few years, the widespread use of 3D printing technology enables the growth of the market of 3D printed products. On Esty, a website focused on handmade items, hundreds of individual entrepreneurs are selling their 3D printed products. Inspired by the positive effects of machine-readable tags, like barcodes, on daily product marketing, we propose AnisoTag, a novel tagging method to encode data on the 2D surface of 3D printed objects based on reflection anisotropy. AnisoTag has an unobtrusive appearance and much lower extraction computational complexity, contributing to a lightweight low-cost tagging system for individual entrepreneurs. On AnisoTag, data are encoded by the proposed tool as reflective anisotropic microstructures, which would reflect distinct illumination patterns when irradiating by collimated laser. Based on it, we implement a real-time detection prototype with inexpensive hardware to determine the reflected illumination pattern and decode data according to their mapping. We evaluate AnisoTag with various 3D printer brands, filaments, and printing parameters, demonstrating its superior usability, accessibility, and reliability for practical usage.

Keywords

Cite

@article{arxiv.2301.10599,
  title  = {AnisoTag: 3D Printed Tag on 2D Surface via Reflection Anisotropy},
  author = {Zehua Ma and Hang Zhou and Weiming Zhang},
  journal= {arXiv preprint arXiv:2301.10599},
  year   = {2023}
}

Comments

To be published in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23), April 23--28, 2023, Hamburg, Germany

R2 v1 2026-06-28T08:19:55.051Z