Skip to search boxSkip to navigationSkip to main content

Adaptive depth map estimation from 3D integral image

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

Abstract

Integral Imaging (InIm) is one of the most promising technologies for producing full color 3-D images with full parallax. InIm requires only one recording in obtaining 3D information and therefore no calibration is necessary to acquire depth values. The compactness of using InIm in depth measurement has been attracting attention as a novel depth extraction technique. In this paper, an algorithm for depth extraction that builds on previous work by the authors is presented. Three main problems in depth map estimation from InIm have been solved; the uncertainty and region homogeneity at image location where errors commonly appear in disparity process, dissimilar displacements within the matching block around object borders, object segmentation. This method is based on the distribution of the sample variance in sub-dividing non-overlapping blocks. A descriptor which is unique and distinctive for each feature on InIm has been achieved. Comparing to state-of-the-art techniques, it is shown that the proposed algorithm has improvements on two aspects: depth map extraction level, computational complexity.

Publication Information

Output type

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

Original language

English

Publication milestones

  • Published - 01/06/2013

Publication status

Published - 01/06/2013

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

ISBN (Electronic)

9781467360470

External Publication IDs

  • handle.net: 10547/334808
  • Scopus: 84887848843

Host publication title

2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

Access to documents

Publication metrics