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A Contour Completion Model for Augmenting Surface Reconstructions

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Part of the book series:Lecture Notes in Computer Science ((LNIP,volume 8691))

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Abstract

The availability of commodity depth sensors such as Kinect has enabled development of methods which can densely reconstruct arbitrary scenes. While the results of these methods are accurate and visually appealing, they are quite often incomplete. This is either due to the fact that only part of the space was visible during the data capture process or due to the surfaces being occluded by other objects in the scene. In this paper, we address the problem of completing and refining such reconstructions. We propose a method for scene completion that can infer the layout of the complete room and the full extent of partially occluded objects. We propose a new probabilistic model, Contour Completion Random Fields, that allows us to complete the boundaries of occluded surfaces. We evaluate our method on synthetic and real world reconstructions of 3D scenes and show that it quantitatively and qualitatively outperforms standard methods. We created a large dataset of partial and complete reconstructions which we will make available to the community as a benchmark for the scene completion task. Finally, we demonstrate the practical utility of our algorithm via an augmented-reality application where objects interact with the completed reconstructions inferred by our method.

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Author information

Authors and Affiliations

  1. Courant Institute, New York University, USA

    Nathan Silberman

  2. Microsoft Research, USA

    Lior Shapira & Ran Gal

  3. Microsoft Research, Cambridge, UK

    Pushmeet Kohli

Authors
  1. Nathan Silberman

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  2. Lior Shapira

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  3. Ran Gal

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  4. Pushmeet Kohli

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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Toront, 6 King’s College Road, M5H 3S5, Toronto, ON, Canada

    David Fleet

  2. Faculty of Electrical Engineering, Department of Cybernetics, Czech Technical University in Prague, Technicka 2, 166 27, Prague 6, Czech Republic

    Tomas Pajdla

  3. Max-Planck-Institut für Informatik, Campus E1 4, 66123, Saarbrücken, Germany

    Bernt Schiele

  4. ESAT - PSI, iMinds, KU Leuven, Kasteelpark Arenberg 10, Bus 2441, 3001, Leuven, Belgium

    Tinne Tuytelaars

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© 2014 Springer International Publishing Switzerland

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Silberman, N., Shapira, L., Gal, R., Kohli, P. (2014). A Contour Completion Model for Augmenting Surface Reconstructions. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds) Computer Vision – ECCV 2014. ECCV 2014. Lecture Notes in Computer Science, vol 8691. Springer, Cham. https://doi.org/10.1007/978-3-319-10578-9_32

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