Rapid Light Field Depth Estimation with Semi-Global Matching
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Running time of the light field depth estimation algorithms is typically high. This assessment is based on the computational complexity of existing methods and the large amounts of data involved. The aim of our work is to develop a simple and fast algorithm for accurate depth computation. In this context, we propose an approach, which involves Semi-Global Matching for the processing of light field images. It forms on comparison of pixels' correspondences with different metrics in the substantially bounded light field space. We show that our method is suitable for the fast production of a proper result in a variety of light field configurations
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DSER: Spectral Epipolar Representation for Efficient Light Field Depth Estimation
DSER combines spectral epipolar regularization with a hybrid pipeline of gradient initialization, plane-sweeping, multiscale refinement, and occlusion-aware random walk to produce structurally consistent depth maps fr...
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