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Real-Time Dense Geometry from a Handheld Camera

  • Jan Stühmer
  • Stefan Gumhold
  • Daniel Cremers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6376)

Abstract

We present a novel variational approach to estimate dense depth maps from multiple images in real-time. By using robust penalizers for both data term and regularizer, our method preserves discontinuities in the depth map. We demonstrate that the integration of multiple images substantially increases the robustness of estimated depth maps to noise in the input images. The integration of our method into recently published algorithms for camera tracking allows dense geometry reconstruction in real-time using a single handheld camera. We demonstrate the performance of our algorithm with real-world data.

Keywords

Input Image Multiple Image Data Term Thresholding Scheme Robust Penalizers 
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

  • Jan Stühmer
    • 1
    • 2
  • Stefan Gumhold
    • 2
  • Daniel Cremers
    • 1
  1. 1.Department of Computer ScienceTU München 
  2. 2.Department of Computer ScienceTU Dresden 

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