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Vol. 6 No. 1 (2020)
Special Issue: Proceedings of CVIS 2020

Articles

Rectification Based Single-Shot Structured Light for Accurate and Dense 3D Reconstruction

https://doi.org/10.15353/jcvis.v6i1.3561

Published 2021-01-15

  • Sina Farsangi
    • ,
  • Mohamed A. Naiel
    • ,
  • Mark Lamm
    • ,
  • Paul Fieguth

Sina Farsangi
University of Waterloo

Mohamed A. Naiel
University of Waterloo

Mark Lamm
Christie Digital Systems Inc.

Paul Fieguth
University of Waterloo

Abstract

Structured Light (SL) patterns generated based on pseudo-random arrays are widely used for single-shot 3D reconstruction using projector-camera systems. These SL images consist of a set of tags with different appearances, where these patterns will be projected on a target surface, then captured by a camera and decoded. The precision of localizing these tags from captured camera images affects the quality of the pixel-correspondences between the projector and the camera, and consequently that of the derived 3D shape. In this paper, we incorporate a quadrilateral representation for the detected SL tags that allows the construction of robust and accurate pixel-correspondences and the application of a spatial rectification module that leads to high tag classification accuracy. When applying the proposed method to single-shot 3D reconstruction, we show the effectiveness of this method over a baseline in estimating denser and more accurate 3D point-clouds.
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