Abstract
Light field cameras capture a scene’s multi-directional light field with one image, allowing the estimation of depth. In this paper, we introduce a fully automatic fast method for depth estimation from a single plenoptic image running a RANSAC-like algorithm for feature matching. The novelty about our approach is the global method to back project correspondences found using photometric similarity to obtain a 3D virtual point cloud. We then use lenses with different focal-lengths in a multiple depth map refining phase and their reprojection to the image plane, generating an accurate depth map per micro lens. Tests with simulations and real images are presented and show a good trade-off between computation time and accuracy of the method presented. Our method achieves an accuracy similar to the state-of-the-art in considerable less time (speedups of around 3 times).
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