PublicationDetail

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

M. Slavcheva, W. Kehl, N. Navab, S. Ilic
SDF-2-SDF: Highly Accurate 3D Object Reconstruction
European Conference on Computer Vision (ECCV), Amsterdam, The Netherlands, October 2016 (supplementary) (bib)

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.
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