Super-rays for Efficient Light Field Processing

Matthieu Hog 1 Neus Sabater 1 Christine Guillemot 2
2 Sirocco - Analysis representation, compression and communication of visual data
Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : 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.
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Matthieu Hog, Neus Sabater, Christine Guillemot. Super-rays for Efficient Light Field Processing. IEEE Journal of Selected Topics in Signal Processing, IEEE, 2017, ⟨10.1109/JSTSP.2017.2738619⟩. ⟨hal-01407852v2⟩

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