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arXiv · 1609.01499

Depth Estimation Through a Generative Model of Light Field Synthesis

Mehdi S. M. Sajjadi·Rolf Köhler·Bernhard Schölkopf·Michael Hirsch
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Abstract

Light field photography captures rich structural information that may facilitate a number of traditional image processing and computer vision tasks. A crucial ingredient in such endeavors is accurate depth recovery. We present a novel framework that allows the recovery of a high quality continuous depth map from light field data. To this end we propose a generative model of a light field that is fully parametrized by its corresponding depth map. The model allows for the integration of powerful regularization techniques such as a non-local means prior, facilitating accurate depth map estimation.

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Mehdi S. M. Sajjadi, Rolf Köhler, Bernhard Schölkopf, Michael Hirsch. 2016-09-06. Depth Estimation Through a Generative Model of Light Field Synthesis. https://doi.org/10.1007/978-3-319-45886-1_35

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