Occlusion-Aware Depth Estimation Using Sparse Light Field Coding

  • Ole Johannsen
  • Antonin SulcEmail author
  • Bastian Goldluecke
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9796)


Disparity estimation for multi-layered light fields can robustly be performed with a statistical analysis of sparse light field coding coefficients [7]. The key idea is to explain each epipolar plane image patch with a dictionary composed of atoms with known disparity values. We significantly improve upon their approach in two ways. First, we reduce the number of necessary dictionary atoms, improving descriptive quality of each and reducing time complexity by an order of magnitude. Second, we introduce a way to explicitly handle occlusions, which is the main drawback in the previous work. Experiments demonstrate that we thus achieve substantially better results on both Lambertian as well as multi-layered scenes.


Light Field Sparse Code Dictionary Learning Center View Disparity Estimate 
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.



This work was supported by the ERC Starting Grant “Light Field Imaging and Analysis” (LIA 336978, FP7-2014).


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Ole Johannsen
    • 1
  • Antonin Sulc
    • 1
    Email author
  • Bastian Goldluecke
    • 1
  1. 1.University of KonstanzKonstanzGermany

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