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Description
  • One of the main drawbacks of Bidirectional Texture Function (BTF), as a method of capturing realistic and accurate real-world material appearance, is the resulting size of the measured data set. Several lossy methods to compress the data were proposed over the years to cope with this problem. To efficiently use the compressed data an appropriate decompression algorithms are also needed, allowing fast random synthesis of BTF data without the need to reconstruct the whole BTF back to its original representation. One of such methods based on multi-level vector quantization and providing both good compression ratio and random access from the compressed data was proposed by Havran et al. in 2010. In this paper, we would like to share our experience with writing a GPU based implementation of the decompression part of the aforementioned method. Our goal was to evaluate the implementation difficulty, as well as the resulting performance and suitability of the algorithm for real-time use.
  • One of the main drawbacks of Bidirectional Texture Function (BTF), as a method of capturing realistic and accurate real-world material appearance, is the resulting size of the measured data set. Several lossy methods to compress the data were proposed over the years to cope with this problem. To efficiently use the compressed data an appropriate decompression algorithms are also needed, allowing fast random synthesis of BTF data without the need to reconstruct the whole BTF back to its original representation. One of such methods based on multi-level vector quantization and providing both good compression ratio and random access from the compressed data was proposed by Havran et al. in 2010. In this paper, we would like to share our experience with writing a GPU based implementation of the decompression part of the aforementioned method. Our goal was to evaluate the implementation difficulty, as well as the resulting performance and suitability of the algorithm for real-time use. (en)
Title
  • Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization
  • Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization (en)
skos:prefLabel
  • Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization
  • Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization (en)
skos:notation
  • RIV/68407700:21230/13:00211050!RIV14-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GAP202/12/2413), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 72067
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/13:00211050
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • BTF; bidirectional texture function; decompression; GPU; OpenCL; Multi-level vector quantization (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [35ED7F017F74]
http://linked.open...v/mistoKonaniAkce
  • Smolenice
http://linked.open...i/riv/mistoVydani
  • Vienna
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 17th Central European Seminar on Computer Graphics
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Egert, Petr
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Institute of Computer Graphics and Algorithms
https://schema.org/isbn
  • 978-3-9502533-5-1
http://localhost/t...ganizacniJednotka
  • 21230
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