Super-rays for Efficient Light Field Processing

Matthieu Hog (1, 2) , Neus Sabater (1) , Christine Guillemot (2)

1 Technicolor R & I [Cesson Sévigné]
2 Sirocco - Analysis representation, compression and communication of visual data

Light field acquisition devices allow capturing scenes with unmatched post-processing possibilities. However, the huge amount of high dimensional data poses challenging problems to light field processing in interactive time. In order to enable light field processing with a tractable complexity, in this paper, we address the problem of light field over-segmentation. We introduce the concept of super-ray, which is a grouping of rays within and across views, as a key component of a light field processing pipeline. The proposed approach is simple, fast, accurate, easily parallelisable, and does not need a dense depth estimation. We demonstrate experimentally the efficiency of the proposed approach on real and synthetic datasets, for sparsely and densely sampled light fields. As super-rays capture a coarse scene geometry information, we also present how they can be used for real time light field segmentation and correcting refocusing angular aliasing.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Matthieu Hog, Neus Sabater, Christine Guillemot. Super-rays for Efficient Light Field Processing. 2016. ⟨hal-01407852v1⟩