Abstract
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.
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Acknowledgements
This work was supported by the ERC Starting Grant “Light Field Imaging and Analysis” (LIA 336978, FP7-2014).
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Johannsen, O., Sulc, A., Goldluecke, B. (2016). Occlusion-Aware Depth Estimation Using Sparse Light Field Coding. In: Rosenhahn, B., Andres, B. (eds) Pattern Recognition. GCPR 2016. Lecture Notes in Computer Science(), vol 9796. Springer, Cham. https://doi.org/10.1007/978-3-319-45886-1_17
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DOI: https://doi.org/10.1007/978-3-319-45886-1_17
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