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A Geometric Perspective on Structured Light Coding

  • Mohit Gupta
  • Nikhil Nakhate
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11220)

Abstract

We present a mathematical framework for analysis and design of high-performance structured light (SL) coding schemes. Using this framework, we design Hamiltonian SL coding, a novel family of SL coding schemes that can recover 3D shape with high precision, with only a small number (as few as three) of images. We establish structural similarity between popular discrete (binary) SL coding methods, and Hamiltonian coding, which is a continuous coding approach. Based on this similarity, and by leveraging design principles from several different SL coding families, we propose a general recipe for designing Hamiltonian coding patterns with specific desirable properties, such as patterns with high spatial frequencies for dealing with global illumination. We perform several experiments to evaluate the proposed approach, and demonstrate that Hamiltonian coding based SL approaches outperform existing methods in challenging scenarios, including scenes with dark albedos, strong ambient light, and interreflections.

Notes

Acknowledgement

This research was supported in parts by the ONR grant number N00014-16-1-2995, and the DARPA REVEAL program.

Supplementary material

474218_1_En_6_MOESM1_ESM.pdf (4 mb)
Supplementary material 1 (pdf 4047 KB)

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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Computer SciencesUniversity of Wisconsin-MadisonMadisonUSA

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