Publication Details

Efficient Random-Access GPU Video Decoding for Light-Field Rendering

CHLUBNA Tomáš, ZEMČÍK Pavel and MILET Tomáš. Efficient Random-Access GPU Video Decoding for Light-Field Rendering. Journal of Visual Communication and Image Representation, vol. 2024, no. 102, pp. 1-14. ISSN 1047-3203. Available from: https://www.sciencedirect.com/science/article/pii/S1047320324001561
Czech title
Efektivní video dekódování s náhodným přístupem na GPU pro light field rendering
Type
journal article
Language
english
Authors
URL
Keywords

light field, video decoding, GPU acceleration, image-based rendering

Abstract

Compression method for GPU streaming of discrete light fields is proposed in this paper. Views on the scene are encoded with video codec to enable streaming in real time. Instead of using a classic scheme, all frames are encoded according to one reference frame. Any frame is decoded directly, in a random-access manner that is suitable for light-field rendering methods, where only few frames are necessary on the GPU. The proposed scheme reaches the best decoding quality/time ratio in comparison to other schemes, where all preceding frames need to be decompressed, and all-key-frame video that supports random access, but is extremely large. The proposed method solves the space-requirements and streaming-bandwidth issues using the GPU accelerated decoding, and enables incorporating light-field assets in real-time 3D simulations. Compared to existing methods, the proposal is easy to implement, does not depend on specific video format or extension and is efficient on consumer GPUs.

Published
2024
Pages
1-14
Journal
Journal of Visual Communication and Image Representation, vol. 2024, no. 102, ISSN 1047-3203
Publisher
Elsevier Science
DOI
UT WoS
001258796500001
EID Scopus
BibTeX
@ARTICLE{FITPUB13227,
   author = "Tom\'{a}\v{s} Chlubna and Pavel Zem\v{c}\'{i}k and Tom\'{a}\v{s} Milet",
   title = "Efficient Random-Access GPU Video Decoding for Light-Field Rendering",
   pages = "1--14",
   journal = "Journal of Visual Communication and Image Representation",
   volume = 2024,
   number = 102,
   year = 2024,
   ISSN = "1047-3203",
   doi = "10.1016/j.jvcir.2024.104201",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/13227"
}
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