• Media type: E-Article
  • Title: Nonlinear Optimization of Light Field Point Cloud
  • Contributor: Anisimov, Yuriy; Rambach, Jason Raphael; Stricker, Didier
  • imprint: MDPI AG, 2022
  • Published in: Sensors
  • Language: English
  • DOI: 10.3390/s22030814
  • ISSN: 1424-8220
  • Keywords: Electrical and Electronic Engineering ; Biochemistry ; Instrumentation ; Atomic and Molecular Physics, and Optics ; Analytical Chemistry
  • Origination:
  • Footnote:
  • Description: <jats:p>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.</jats:p>
  • Access State: Open Access