2.50
Hdl Handle:
http://hdl.handle.net/10547/334808
Title:
Adaptive depth map estimation from 3D integral image
Authors:
Alazawi, E.; Aggoun, Amar; Abbod, M.; Fatah, O. Abdul; Swash, M.R.
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.
Affiliation:
Brunel University; University of Bedfordshire
Citation:
Alazawi, E., Aggoun, A., Abbod, M., Fatah, O.A., Swash, M.R. (2013) 'Adaptive depth map estimation from 3D integral image'. IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), London, 5th - 7th June
Publisher:
IEEE
Issue Date:
Jun-2013
URI:
http://hdl.handle.net/10547/334808
DOI:
10.1109/BMSB.2013.6621736
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6621736
Type:
Conference papers, meetings and proceedings
Language:
en
ISSN:
2155-5044
Sponsors:
This work was supported by European Commission under FP7-ICT-2009-4 (3DVIVANT).
Appears in Collections:
Centre for Computer Graphics and Visualisation (CCGV)

Full metadata record

DC FieldValue Language
dc.contributor.authorAlazawi, E.en
dc.contributor.authorAggoun, Amaren
dc.contributor.authorAbbod, M.en
dc.contributor.authorFatah, O. Abdulen
dc.contributor.authorSwash, M.R.en
dc.date.accessioned2014-11-13T09:47:16Z-
dc.date.available2014-11-13T09:47:16Z-
dc.date.issued2013-06-
dc.identifier.citationAlazawi, E., Aggoun, A., Abbod, M., Fatah, O.A., Swash, M.R. (2013) 'Adaptive depth map estimation from 3D integral image'. IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), London, 5th - 7th Juneen
dc.identifier.issn2155-5044-
dc.identifier.doi10.1109/BMSB.2013.6621736-
dc.identifier.urihttp://hdl.handle.net/10547/334808-
dc.description.abstractIntegral 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.en
dc.description.sponsorshipThis work was supported by European Commission under FP7-ICT-2009-4 (3DVIVANT).en
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6621736en
dc.subject3D integral imageen
dc.subjectautomatic thresholden
dc.subjectdisparity depth mapen
dc.subjectfeature based matchingen
dc.subjectk-NN majority voteen
dc.subjectviewpoints imagesen
dc.subjectadaptive estimationen
dc.subjectcomputational complexityen
dc.subjectfeature extractionen
dc.subjectimage colour analysisen
dc.subjectimage matchingen
dc.subjectimage segmentationen
dc.titleAdaptive depth map estimation from 3D integral imageen
dc.typeConference papers, meetings and proceedingsen
dc.contributor.departmentBrunel Universityen
dc.contributor.departmentUniversity of Bedfordshireen
All Items in UOBREP are protected by copyright, with all rights reserved, unless otherwise indicated.