Name
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/BMSB.2013.6621736 | Broadband Multimedia Systems and Broadcasting |
Keywords | Field | DocType |
adaptive estimation,computational complexity,feature extraction,image colour analysis,image matching,image segmentation,3D information,InIm,adaptive depth map estimation,calibration,computational complexity,depth extraction technique,depth measurement,depth value acquisition,disparity process,dissimilar displacement,full color 3D Integral imaging,object border matching block,object segmentation,subdividing non-overlapping block,3D Integral image,Automatic threshold,Disparity depth map,Feature based matching,Viewpoints images,k-NN majority vote | Integral imaging,Computer vision,Parallax,Pattern recognition,Computer science,Segmentation,Feature extraction,Image segmentation,Artificial intelligence,Depth map,Measured depth,Computational complexity theory | Conference |
ISSN | Citations | PageRank |
2155-5044 | 4 | 0.61 |
References | Authors | |
2 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alazawi, E. | 1 | 4 | 0.61 |
| Amar Aggoun | 2 | 115 | 21.34 |
| Maysam F. Abbod | 3 | 224 | 28.14 |
| O. Abdul Fatah | 4 | 5 | 0.97 |