CVJul 31, 2019

Rapid Light Field Depth Estimation with Semi-Global Matching

arXiv:1907.13449v17 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the need for efficient depth estimation in light field imaging, which is incremental as it applies an existing method to a specific domain.

The paper tackled the problem of high computational time in light field depth estimation by proposing a fast algorithm using Semi-Global Matching, achieving accurate depth computation suitable for various configurations.

Running time of the light field depth estimation algorithms is typically high. This assessment is based on the computational complexity of existing methods and the large amounts of data involved. The aim of our work is to develop a simple and fast algorithm for accurate depth computation. In this context, we propose an approach, which involves Semi-Global Matching for the processing of light field images. It forms on comparison of pixels' correspondences with different metrics in the substantially bounded light field space. We show that our method is suitable for the fast production of a proper result in a variety of light field configurations

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