Datasets and Benchmarks for Densely Sampled 4D Light Fields

Abstract

We present a new benchmark database to compare and evaluate existing and upcoming algorithms which are tailored to light field processing. The data is characterised by a dense sampling of the light fields, which best fits current plenoptic cameras and is a characteristic property not found in current multi-view stereo benchmarks. It allows to treat the disparity space as a continuous space, and enables algorithms based on epipolar plane image analysis without having to refocus first. All datasets provide ground truth depth for at least the center view, while some have additional segmentation data available. Part of the light fields are computer graphics generated, the rest are acquired with a gantry, with ground truth depth established by a previous scanning of the imaged objects using a structured light scanner. In addition, we provide source code for an extensive evaluation of a number of previously published stereo, epipolar plane image analysis and segmentation algorithms on the database.