An appearance uniformity metric for 3D printing

Michael Ludwig, Gary Meyer, Ingeborg Tastl, Nathan Moroney, Melanie Gottwals

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


A method is presented for perceptually characterizing appearance non-uniformities that result from 3D printing. In contrast to physical measurements, the model is designed to take into account the human visual system and variations in observer conditions such as lighting, point of view, and shape. Additionally, it is capable of handling spatial reectance variations over a material’s surface. Motivated by Schrödinger’s line element approach to studying color dierences, an image-based psychophysical experiment that explores paths between materials in appearance space is conducted. The line element concept is extended from color to spatially-varying appearances–including color, roughness and gloss-which enables the measurement of ne dierences between appearances along a path. We dene two path functions, one interpolating reectance parameters and the other interpolating the nal imagery. An image-based uniformity model is developed, applying a trained neural network to color dierences calculated from rendered images of the printed non-uniformities. The nal model is shown to perform better than commonly used image comparison algorithms, including spatial pattern classes that were not used in training.

Original languageEnglish (US)
Title of host publicationProceedings - SAP 2018
Subtitle of host publicationACM Symposium on Applied Perception
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450358941
StatePublished - Aug 10 2018
Event15th International ACM Symposium on Applied Perception, SAP 2018 - Vancouver, Canada
Duration: Aug 10 2018Aug 11 2018

Publication series

NameProceedings - SAP 2018: ACM Symposium on Applied Perception


Other15th International ACM Symposium on Applied Perception, SAP 2018

Bibliographical note

Publisher Copyright:
© 2018 Association for Computing Machinery.


  • 3D printing
  • Appearance uniformity
  • Neural networks
  • Spatially-varying appearance perception


Dive into the research topics of 'An appearance uniformity metric for 3D printing'. Together they form a unique fingerprint.

Cite this