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Belief Propagation for Improved Color Assessment in Structured Light

  • Christoph Schmalz
  • Elli Angelopoulou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6376)

Abstract

Single-Shot Structured Light is a well-known method for acquiring 3D surface data of moving scenes with simple and compact hardware setups. Some of the biggest challenges in these systems is their sensitivity to textured scenes, subsurface scattering and low-contrast illumination. Recently, a graph-based method has been proposed that largely eliminates these shortcomings. A key step in the graph-based pattern decoding algorithm is the estimation of color of local image regions which correspond to the vertex colors of the graph. In this work we propose a new method for estimating the color of a vertex based on belief propagation (BP). The BP framework allows the explicit inclusion of cues from neigboring vertices in the color estimation. This is especially beneficial for low-contrast input images. The augmented method is evaluated using typical low-quality real-world test sequences of the interior of a pig stomach. We demonstrate a significant improvement in robustness. The number of 3D data points generated increases by 30 to 50 percent over the plain decoding.

Keywords

Belief Propagation Texture Scene Color Enhancement Projected Color Subsurface Scattering 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Christoph Schmalz
    • 1
    • 2
  • Elli Angelopoulou
    • 1
  1. 1.Pattern Recognition LabUniversity of Erlangen-NurembergGermany
  2. 2.Siemens CT T HW 2MunichGermany

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