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G-ID: identifying 3D Prints using slicing parameters
conference contribution
posted on 2023-06-09, 20:23 authored by Mustafa Doga Dogan, Faraz Faruqi, Andrew Day Churchill, Kenneth Friedman, Leon Cheng, Sriram Subramanian, Stefanie MuellerWe 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.
Funding
Manipulating Acoustic wavefronts using metamaterials for novel user interfaces; G2388; EUROPEAN UNION; 787413
History
Publication status
- Published
File Version
- Accepted version
Journal
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI 2020)Publisher
ACMExternal DOI
Page range
1-13Event name
ACM CHI Conference on Human Factors in Computing Systems (CHI 2020)Event location
Honolulu, Hawaii, USAEvent type
conferenceEvent date
25 - 30 April, 2020Place of publication
Honolulu HI USAISBN
9781450367080Department affiliated with
- Informatics Publications
Research groups affiliated with
- Creative Technology Publications
Notes
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.Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2020-01-24First Open Access (FOA) Date
2020-04-28First Compliant Deposit (FCD) Date
2020-01-23Usage metrics
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