Result Details

Real-Time Light Field Video Focusing and GPU Accelerated Streaming

CHLUBNA, T.; MILET, T.; ZEMČÍK, P.; KULA, M. Real-Time Light Field Video Focusing and GPU Accelerated Streaming. Journal of Signal Processing Systems for Signal Image and Video Technology, 2023, vol. 95, no. 6, p. 703-719. ISSN: 1939-8115.
Type
journal article
Language
English
Authors
Abstract

This paper proposes a novel solution of real-time depth range and correct focusing estimation in light field videos represented by arrays of video sequences. This solution, compared to previous approaches, offers a novel way to render high-quality synthetic views from light field videos on contemporary hardware in real-time. Only the video frames containing color information with no other attributes, such as captured depth, are needed. The drawbacks of the previous proposals such as block artifacts in the defocused parts of the scene or manual setting of the depth range are also solved in this paper. This paper describes a complete solution that solves the main memory and performance issues of light field rendering on contemporary personal computers. The whole integration of high-quality light field videos supersedes the approaches in previous works and the paper also provides measurements and experimental results. While reaching the same quality as slower state-of-the-art approaches, this method can still be used in real-time which makes it suitable for industry and real-life scenarios as an alternative to standard 3D rendering approaches.

Keywords

Light field, GPU, Image-based rendering

URL
Published
2023
Pages
703–719
Journal
Journal of Signal Processing Systems for Signal Image and Video Technology, vol. 95, no. 6, ISSN 1939-8115
DOI
UT WoS
000991328300001
EID Scopus
BibTeX
@article{BUT185176,
  author="Tomáš {Chlubna} and Tomáš {Milet} and Pavel {Zemčík} and Michal {Kula}",
  title="Real-Time Light Field Video Focusing and GPU Accelerated Streaming",
  journal="Journal of Signal Processing Systems for Signal Image and Video Technology",
  year="2023",
  volume="95",
  number="6",
  pages="703--719",
  doi="10.1007/s11265-023-01874-8",
  issn="1939-8018",
  url="https://link.springer.com/article/10.1007/s11265-023-01874-8"
}
Projects
AI-augmented automation for efficient DevOps, a model-based framework for continuous development At RunTime in cyber-physical systems, EU, Horizon 2020, 8A21015, 101007350, start: 2021-04-01, end: 2024-03-31, running
Soudobé metody zpracování, analýzy a zobrazování multimediálních a 3D dat, BUT, Vnitřní projekty VUT, FIT-S-23-8278, start: 2023-03-01, end: 2026-02-28, running
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