Surface Reconstruction from Multi-Resolution Sample Points

This website provides material for the surface reconstruction algorithm described in the following paper:

Surface Reconstruction from Multi-Resolution Sample Points [Paper, 8MB] [Code]
Patrick Mücke, Ronny Klowsky and Michael Goesele
In: Proceedings of Vision, Modeling, and Visualization (VMV 2011), Berlin, Germany, October 4-6, 2011.
Teaser

Paper Abstract

Robust surface reconstruction from sample points is a challenging problem, especially for real-world input data. We significantly improve on a recent method by Hornung and Kobbelt [HK06b] by implementing three major extensions. First, we exploit the footprint information inherent to each sample point, that describes the underlying surface region represented by that sample. We interpret each sample as a vote for a region in space where the size of the region depends on the footprint size. In our method, sample points with large footprints do not destroy the fine detail captured by sample points with small footprints. Second, we propose a new crust computation making the method applicable to a substantially broader range of input data. This includes data from objects that were only partially sampled, a common case for data generated by multi-view stereo applied to Internet images. Third, we adapt the volumetric resolution locally to the footprint size of the sample points which allows to extract fine detail even in large-scale scenes. The effectiveness of our extensions is shown on challenging outdoor data sets as well as on a standard benchmark.

Source Code

The code is now available for download. For compilation and usage please consult the readme.txt in the zip package.

Download

Version 1.01: zip [5MB]

License and Disclaimer

Copyright © 2012, Patrick Mücke, Ronny Klowsky, Michael Goesele, TU Darmstadt.

Redistribution and use in source and binary forms, with or without modification, are permitted for non-commercial research purposes only provided that the following conditions are met:

  • Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

Please contact a copyright holder if you require a different license.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The package contains the publicly available graph cut library MAXFLOW by Boykov and Kolmogorov in version 3.01