Scene depth extraction from Holoscopic Imaging technology

3D Holoscopic Imaging (3DHI) is a promising technique for viewing natural continuous parallax 3D objects within a wide viewing zone using the principle of “Fly's eye”. The 3D content is captured using a single aperture camera in real-time and represents a true volume spatial optical model of the object scene. The 3D content viewed by multiple viewers independently of their position, without 3D eyewear glasses. The 3DHI technique merely requires a single recording that the acquisition of the 3D information and the compactness of depth measurement that is used has been attracting attention as a novel depth extraction technique. This paper presents a new corresponding and matching technique based on a novel automatic Feature-Match Selection (FMS) algorithm. The aim of this algorithm is to estimate and extract an accurate full parallax 3D model form from a 3D Omni-directional Holoscopic Imaging (3DOHI) system. The basis for the novelty of the paper is on two contributions: feature blocks selection and corresponding automatic optimization process. There are solutions for three main problems related to the depth map estimation from 3DHI: uncertainty and region homogeneity at image location, dissimilar displacements within the matching block around object borders, and computational complexity.