Publikation

Nonlinear Optimization of Light Field Point Cloud

Yuriy Anisimov, Jason Raphael Rambach, Didier Stricker

In: Academic Editor Denis Laurendeau (Hrsg.). Sensors - Open Access Journal (Sensors) 22(3) Seiten 814-829 MDPI 1/2022.

Abstrakt

The problem of accurate three-dimensional reconstruction is important for many research and industrial applications. Light field depth estimation utilizes many observations of the scene and hence can provide accurate reconstruction. We present a method, which enhances existing reconstruction algorithm with per-layer disparity filtering and consistency-based holes filling. Together with that we reformulate the reconstruction result to a form of point cloud from different light field viewpoints and propose a non-linear optimization of it. The capability of our method to reconstruct scenes with acceptable quality was verified by evaluation on a publicly available dataset.

Projekte

Weitere Links

sensors-22-00814.pdf (pdf, 4 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence