SAIL: Semantic Analysis of Information in Light Fields: Results from Synthetic and Real-World Data

Abstract

Computational photography has revolutionized the way we capture and interpret images. Light fields, in particular, offer a rich representation of a scene"s geometry and appearance by encoding both spatial and angular information. In this paper, we present a novel approach to light field analysis that focuses on semantics. In contrast to the uniform distribution of samples in two-dimensional images, the distribution of samples in light fields varies for different scene regions. Some points are sampled from multiple directions, while others may only be captured by a small portion of the light field array. Our approach provides insights into this non-uniform distribution and helps guide further processing steps to fully leverage the available information content.