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Scene depth extraction from Holoscopic Imaging technology

  • E. Alazawi
    ,
  • Amar Aggoun
    ,
  • M. Abbod
    ,
  • M.R. Swash
    ,
  • O. Abdul Fatah
    ,
  • Juan C. J. Fernandez
  • Brunel University London
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

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.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Publication milestones

  • Published - 02/12/2013

Publication status

Published - 02/12/2013

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

ISBN (Print)

9781479913695

ISBN (Electronic)

9781479913695

External Publication IDs

  • handle.net: 10547/334483
  • Scopus: 84898919231

Host publication title

2013 3DTV Vision Beyond Depth (3DTV-CON)

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