A streamlined photometric stereo framework for cultural heritage

Chia Kai Yeh*, Nathan Matsuda, Xiang Huang, Fengqiang Li, Marc Sebastian Walton, Oliver Strides Cossairt

*Corresponding author for this work

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

6 Scopus citations

Abstract

In this paper, we propose a streamlined framework of robust 3D acquisition for cultural heritage using both photometric stereo and photogrammetric information. An uncalibrated photometric stereo setup is augmented by a synchronized secondary witness camera co-located with a point light source. By recovering the witness camera’s position for each exposure with photogrammetry techniques, we estimate the precise 3D location of the light source relative to the photometric stereo camera. We have shown a significant improvement in both light source position estimation and normal map recovery compared to previous uncalibrated photometric stereo techniques. In addition, with the new configuration we propose, we benefit from improved surface shape recovery by jointly incorporating corrected photometric stereo surface normals and a sparse 3D point cloud from photogrammetry.

Original languageEnglish (US)
Title of host publicationComputer Vision - ECCV 2016 Workshops, Proceedings
EditorsGang Hua, Hervé Jégou
PublisherSpringer Verlag
Pages738-752
Number of pages15
ISBN (Print)9783319466033
DOIs
StatePublished - Jan 1 2016
Event14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands
Duration: Oct 8 2016Oct 16 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9913 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th European Conference on Computer Vision, ECCV 2016
CountryNetherlands
CityAmsterdam
Period10/8/1610/16/16

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Keywords

  • 3D surface shape Reconstruction
  • Near light position calibration
  • Photogrammetry
  • Photometric stereo
  • Reflectance transformation imaging

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Yeh, C. K., Matsuda, N., Huang, X., Li, F., Walton, M. S., & Cossairt, O. S. (2016). A streamlined photometric stereo framework for cultural heritage. In G. Hua, & H. Jégou (Eds.), Computer Vision - ECCV 2016 Workshops, Proceedings (pp. 738-752). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9913 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46604-0_51