Light Field Depth Estimation via Stitched Epipolar Plane Images
Ping Zhou, Langqing Shi, Xiaoyang Liu, Jing Jin, Yuting Zhang, and, Junhui Hou

TL;DR
This paper introduces a novel stitched-EPI approach for light field depth estimation, improving accuracy in slope computation, occlusion handling, and texture-less regions, resulting in more precise depth maps.
Contribution
It proposes the stitched-EPI concept, the half-SEPI algorithm for occlusion, and a depth propagation strategy, advancing the accuracy and robustness of light field depth estimation.
Findings
Outperforms state-of-the-art methods in accuracy
Enhances depth estimation in occluded and texture-less regions
Validated through extensive experiments and ablation studies
Abstract
Depth estimation is a fundamental problem in light field processing. Epipolar-plane image (EPI)-based methods often encounter challenges such as low accuracy in slope computation due to discretization errors and limited angular resolution. Besides, existing methods perform well in most regions but struggle to produce sharp edges in occluded regions and resolve ambiguities in texture-less regions. To address these issues, we propose the concept of stitched-EPI (SEPI) to enhance slope computation. SEPI achieves this by shifting and concatenating lines from different EPIs that correspond to the same 3D point. Moreover, we introduce the half-SEPI algorithm, which focuses exclusively on the non-occluded portion of lines to handle occlusion. Additionally, we present a depth propagation strategy aimed at improving depth estimation in texture-less regions. This strategy involves determining the…
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Taxonomy
TopicsAdvanced Vision and Imaging · Optical measurement and interference techniques · Image Enhancement Techniques
