Photometric Segmentation: Simultaneous Photometric Stereo and Masking

Bjoern Haefner, Yvain Queau, Daniel Cremers

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

This work is concerned with both the 3D-reconstruction of an object using photometric stereo, and its 2D-segmentation from the background. In contrast with previous works on photometric stereo which assume that a mask of the area of interest has been computed beforehand, we formulate 3D-reconstruction and 2D-segmentation as a joint problem. The proposed variational solution combines a differential formulation of photometric stereo with the classic Chan-Vese model for active contours. Given a set of photometric stereo images, this solution simultaneously infers a binary mask of the object of interest and a depth map representing its 3D-shape. Experiments on real-world datasets confirm the soundness of simultaneously solving both these classic computer vision problems, as the joint approach considerably simplifies the overall 3D-scanning process for the end-user.

Original languageEnglish
Title of host publicationProceedings - 2019 International Conference on 3D Vision, 3DV 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages222-229
Number of pages8
ISBN (Electronic)9781728131313
DOIs
StatePublished - Sep 2019
Event7th International Conference on 3D Vision, 3DV 2019 - Quebec, Canada
Duration: 15 Sep 201918 Sep 2019

Publication series

NameProceedings - 2019 International Conference on 3D Vision, 3DV 2019

Conference

Conference7th International Conference on 3D Vision, 3DV 2019
Country/TerritoryCanada
CityQuebec
Period15/09/1918/09/19

Keywords

  • 3D Reconstruction
  • Photometric Stereo
  • Segmentation
  • Variational Methods

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