Edge-preserving photometric stereo via depth fusion

Qing Zhang, Mao Ye, Ruigang Yang, Yasuyuki Matsushita, Bennett Wilburn, Huimin Yu

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

58 Scopus citations

Abstract

We present a sensor fusion scheme that combines active stereo with photometric stereo. Aiming at capturing full-frame depth for dynamic scenes at a minimum of three lighting conditions, we formulate an iterative optimization scheme that (1) adaptively adjusts the contribution from photometric stereo so that discontinuity can be preserved; (2) detects shadow areas by checking the visibility of the estimated point with respect to the light source, instead of using image-based heuristics; and (3) behaves well for ill-conditioned pixels that are under shadow, which are inevitable in almost any scene. Furthermore, we decompose our non-linear cost function into subproblems that can be optimized efficiently using linear techniques. Experiments show significantly improved results over the previous state-of-the-art in sensor fusion.

Original languageEnglish
Title of host publication2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012
Pages2472-2479
Number of pages8
DOIs
StatePublished - 2012
Event2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012 - Providence, RI, United States
Duration: Jun 16 2012Jun 21 2012

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Conference

Conference2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012
Country/TerritoryUnited States
CityProvidence, RI
Period6/16/126/21/12

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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