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Accurate Light Field Depth Estimation Using Multi-Orientation Partial Angular Coherence
- Source :
- IEEE Access, Vol 7, Pp 169123-169132 (2019)
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- Occlusion is a critical issue that affects the accuracy for light field depth estimation. In the presence of occlusions, the photo-consistency property is broken, making ambiguity near occlusion areas. In this paper, we proposed using multi-orientation partial angular coherence to achieve accurate depth estimation by which the occlusions are explicitly treated. Unlike previous approaches, the correspondence is partially measured along several lines with different directions. We show that depending on the occlusion edge orientation, the pixels along the occlusion orientation still preserve photo-consistency. By computing the partial angular coherence in four potential directions, we can obtain a sharp initial depth map. Since occlusions are precisely tackled, the outliers can be mostly removed by fast guided filtering on the cost volume. As a result, the depth accuracy at occlusion boundaries is greatly improved. The proposed method can obtain sharp transition edges at occlusion boundaries and has no requirement for extra edge information. Experimental results on a recent benchmark demonstrate that the proposed method outperforms the state-of-the-art algorithms in the accuracy metrics. Further experiments on real-world scenes also show the superior performance of the proposed method.
- Subjects :
- occlusion handling
General Computer Science
Pixel
Computer science
angular coherence
General Engineering
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Filter (signal processing)
01 natural sciences
010309 optics
Depth map
Computer Science::Computer Vision and Pattern Recognition
0103 physical sciences
Outlier
Computer Science::Multimedia
light field
General Materials Science
lcsh:Electrical engineering. Electronics. Nuclear engineering
Depth estimation
Algorithm
lcsh:TK1-9971
Light field
Coherence (physics)
ComputingMethodologies_COMPUTERGRAPHICS
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 7
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....2c0f6ec3ee38c0bc06d86c7374024a4c