G-ID: identifying 3D Prints using slicing parameters

Doga Dogan, Mustafa, Faruqi, Faraz, Churchill, Andrew Day, Friedman, Kenneth, Cheng, Leon, Subramanian, Sriram and Mueller, Stefanie (2020) G-ID: identifying 3D Prints using slicing parameters. ACM CHI Conference on Human Factors in Computing Systems (CHI 2020), Honolulu, Hawaii, USA, 25 - 30 April, 2020. Published in: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI 2020). 1-13. ACM, Honolulu HI USA. ISBN 9781450367080

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We present G-ID, a method that utilizes the subtle patterns left by the 3D printing process to distinguish and identify objects that otherwise look similar to the human eye. The key idea is to mark different instances of a 3D model by varying slicing parameters that do not change the model geometry but can be detected as machine-readable differences in the print. As a result, G-ID does not add anything to the object but exploits the patterns appearing as a byproduct of slicing, an essential step of the 3D printing pipeline.
We introduce the G-ID slicing & labeling interface that varies the settings for each instance, and the G-ID mobile app, which uses image processing techniques to retrieve the parameters and their associated labels from a photo of the 3D printed object. Finally, we evaluate our method’s accuracy under different lighting conditions, when objects were printed with different filaments and printers, and with pictures taken from various positions and angles.

Item Type: Conference Proceedings
Additional Information: We thank Alexandre Kaspar, Liane Makatura, Danielle Pace, and Jack Forman for the fruitful discussions. This work was supported in part by NSF Award IIS-1716413. Sriram Subramanian is grateful for the ERC Advanced Grant (#787413) and the RAEng Chairs in Emerging Technology Program.
Keywords: personal fabrication, 3D printing, identification, making, tags
Schools and Departments: School of Engineering and Informatics > Informatics
Research Centres and Groups: Creative Technology
Depositing User: Lucy Arnold
Date Deposited: 24 Jan 2020 10:43
Last Modified: 30 Apr 2021 14:24
URI: http://sro.sussex.ac.uk/id/eprint/89517

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Manipulating Acoustic wavefronts using metamaterials for novel user interfacesG2388EUROPEAN UNION787413