4DLFVD

Abstract

We present a 4D Light Field (LF) video dataset, collected by a custom-made camera matrix, to be used for designing and testing algorithms and systems for LF video coding, processing, and streaming. Compared to existing LF datasets, ours provides LF videos, as opposed to only images, and at higher frame resolution, higher number of viewpoints, and/or higher framerate, offering the best visual quality LF video dataset. To achieve this, we built a 10 x 10 LF capture matrix composed of 100 cameras, each with a 1920 x 1056 resolution. We used this matrix to record videos in real and varying illumination and scene dynamics conditions. The dataset contains a total of nine groups of LF videos: eight groups collected with a fixed camera matrix position and orientation recording indoor potted plants, furniture, etc., and the last group collected by rotating around an outdoor environment with roadside vehicles, pedestrians, etc. Each group of LF videos consists of 100 video streams encoded with H.265/HEVC. Scene changes vary from static to slightly dynamic to highly dynamic, providing a good level of diversity. As an example, we present the results of a depth estimation method and show that our dataset can be used for applications such as objection detection, 3D modeling, and others.