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In this paper, we introduce a novel graph representation forinteractive light field segmentation using Markov Random Field (MRF).The greatest barrier to the adoption of MRF for light field processing isthe large volume of input data. The proposed graph structure exploits theredundancy in the ray space in order to reduce the graph size, decreasingthe running time of MRF-based optimisation tasks. Concepts offree raysandray bundleswith corresponding neighbourhood relationships are de-fined to construct the simplified graph-based light field representation.We then propose a light field interactive segmentation algorithm usinggraph-cuts based on such ray space graph structure, that guarantees thesegmentation consistency across all views. Our experiments with severaldatasets show results that are very close to the ground truth, competingwith state of the art light field segmentation methods in terms of accu-racy and with a significantly lower complexity. They also show that ourmethod performs well on both densely and sparsely sampled light fields.
