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SDF-2-SDF: Highly Accurate 3D Object Reconstruction

  • Miroslava SlavchevaEmail author
  • Wadim Kehl
  • Nassir Navab
  • Slobodan Ilic
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9905)

Abstract

This paper addresses the problem of 3D object reconstruction using RGB-D sensors. Our main contribution is a novel implicit-to-implicit surface registration scheme between signed distance fields (SDFs), utilized both for the real-time frame-to-frame camera tracking and for the subsequent global optimization. SDF-2-SDF registration circumvents expensive correspondence search and allows for incorporation of multiple geometric constraints without any dependence on texture, yielding highly accurate 3D models. An extensive quantitative evaluation on real and synthetic data demonstrates improved tracking and higher fidelity reconstructions than a variety of state-of-the-art methods. We make our data publicly available, creating the first object reconstruction dataset to include ground-truth CAD models and RGB-D sequences from sensors of various quality.

Keywords

Object reconstruction Signed distance field RGB-D sensors 

Notes

Acknowledgements

We thank Siemens AG for funding the creation of the 3D printed dataset. We are also grateful to Patrick Wissmann for providing access to the phase shift sensor and to Tolga Birdal for his invaluable help in the image acquisition.

Supplementary material

Supplementary material 1 (avi 2410 KB)

419956_1_En_41_MOESM2_ESM.pdf (17.7 mb)
Supplementary material 2 (pdf 18103 KB)

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Miroslava Slavcheva
    • 1
    • 2
    Email author
  • Wadim Kehl
    • 1
  • Nassir Navab
    • 1
  • Slobodan Ilic
    • 1
    • 2
  1. 1.Technische Universität MünchenMunichGermany
  2. 2.Siemens AGMunichGermany

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