Light Field Segmentation Using a Ray-Based Graph Structure
Résumé
In this paper, we introduce a novel graph representation for
interactive light eld segmentation using Markov Random Field (MRF).
The greatest barrier to the adoption of MRF for light eld processing is
the large volume of input data. The proposed graph structure exploits the
redundancy in the ray space in order to reduce the graph size, decreasing
the running time of MRF-based optimisation tasks. Concepts of free rays
and ray bundles with corresponding neighbourhood relationships are de-
ned to construct the simplied graph-based light eld representation.
We then propose a light eld interactive segmentation algorithm using
graph-cuts based on such ray space graph structure, that guarantees the
segmentation consistency across all views. Our experiments with several
datasets show results that are very close to the ground truth, competing
with state of the art light eld segmentation methods in terms of accuracy
and with a signicantly lower complexity. They also show that our
method performs well on both densely and sparsely sampled light fields.
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