Issue Date
2013-06Subjects
3D integral imageautomatic threshold
disparity depth map
feature based matching
k-NN majority vote
viewpoints images
adaptive estimation
computational complexity
feature extraction
image colour analysis
image matching
image segmentation
Metadata
Show full item recordAbstract
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.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 JunePublisher
IEEEType
Conference papers, meetings and proceedingsLanguage
enISSN
2155-5044Sponsors
This work was supported by European Commission under FP7-ICT-2009-4 (3DVIVANT).ae974a485f413a2113503eed53cd6c53
10.1109/BMSB.2013.6621736