Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00211050" target="_blank" >RIV/68407700:21230/13:00211050 - isvavai.cz</a>
Result on the web
<a href="http://www.cescg.org/CESCG-2013/papers/Egert-Efficient_GPU-based_Decompression_of_BTF_Data_Compressed_using_Multi-Level_Vector_Quantization.pdf" target="_blank" >http://www.cescg.org/CESCG-2013/papers/Egert-Efficient_GPU-based_Decompression_of_BTF_Data_Compressed_using_Multi-Level_Vector_Quantization.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization
Original language 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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GAP202%2F12%2F2413" target="_blank" >GAP202/12/2413: Optimal Algorithms for Image Synthesis</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 17th Central European Seminar on Computer Graphics
ISBN
978-3-9502533-5-1
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
Institute of Computer Graphics and Algorithms
Place of publication
Vienna
Event location
Smolenice
Event date
Apr 28, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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