Calibration of the projector with fixed pattern and large distortion lens in a structured light system

Xingdou Fu, Zuofu Wang, Hiroshi Kawasaki, Ryusuke Sagawa, Ryo Furukawa

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

3 Citations (Scopus)

Abstract

The most critical factor affects accuracy of a Structured Light System (SLS) is calibration. Camera calibration is easy to complete because of its extensive study. To simplify projector calibration, previous wor models the projector as an inverse camera and tries to build similar 3D-2D mapping data for projector calibration. Achieved mapping data is directly fed to some classic two-step camera calibration methods. When projector comes with a large distortion lens, this kind of methods will fail because their first steps use closed-form solution to calculate initial guess for optimization in next steps. We proposed a new method to calibrate the projector by removing its distortion first. Because projector cannot “see” anything, not like camera case, constraints such as “straight lines remain straight” working just on 2D image is invalid for distortion estimation. With 3D-2D mapping data, the estimation will involve several extra unknowns into a non-linear optimization. We use partial mapping data whose 2D points in a “small central area” of projector pattern image to acquire an initial guess for those unknowns, and then use all mapping data to refine them and estimate distortion parameters. Experiments show our method can still calibrate the projector when classic methods fail.

Original languageEnglish
Title of host publicationProceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013
PublisherMVA Organization
Pages222-225
Number of pages4
ISBN (Print)9784901122139
Publication statusPublished - 2013
Externally publishedYes
Event13th IAPR International Conference on Machine Vision Applications, MVA 2013 - Kyoto, Japan
Duration: May 20 2013May 23 2013

Publication series

NameProceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013

Conference

Conference13th IAPR International Conference on Machine Vision Applications, MVA 2013
CountryJapan
CityKyoto
Period5/20/135/23/13

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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