Depth estimation of complex geometry scenes from light fields

Lipeng Si; Qing Wang

doi:10.1117/12.2291596

12 January 2018 Depth estimation of complex geometry scenes from light fields

Lipeng Si, Qing Wang

Proceedings Volume 10620, 2017 International Conference on Optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and Signal Processing Technology; 106200M (2018) https://doi.org/10.1117/12.2291596
Event: International Conference on Optical Instruments and Technology 2017, 2017, Beijing, China

Abstract

The surface camera (SCam) of light fields gathers angular sample rays passing through a 3D point. The consistency of SCams is evaluated to estimate the depth map of scene. But the consistency is affected by several limitations such as occlusions or non-Lambertian surfaces. To solve those limitations, the SCam is partitioned into two segments that one of them could satisfy the consistency constraint. The segmentation pattern of SCam is highly related to the texture of spatial patch, so we enforce a mask matching to describe the shape correlation between segments of SCam and spatial patch. To further address the ambiguity in textureless region, a global method with pixel-wise plane label is presented. Plane label inference at each pixel can recover not only depth value but also local geometry structure, that is suitable for light fields with sub-pixel disparities and continuous view variation. Our method is evaluated on public light field datasets and outperforms the state-of-the-art.

Citation Download Citation

Lipeng Si and Qing Wang "Depth estimation of complex geometry scenes from light fields", Proc. SPIE 10620, 2017 International Conference on Optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and Signal Processing Technology, 106200M (12 January 2018); https://doi.org/10.1117/12.2291596

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KEYWORDS

Cameras

Human-computer interaction

Image segmentation

Silicon

Reflectivity

Binary data

Statistical analysis

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