About: Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Efficient GPU-based Decompression of BTF Data Compressed using Multi-Level Vector Quantization Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://www.cescg.org/CESCG-2013/papers/Egert-Efficient_GPU-based_Decompression_of_BTF_Data_Compressed_using_Multi-Level_Vector_Quantization.pdf
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	P S
http://linked.open...avai/riv/aktivity	P(GAP202/12/2413), S
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Egert, Petr
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	72067
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/13:00211050
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	BTF; bidirectional texture function; decompression; GPU; OpenCL; Multi-level vector quantization (en)
http://linked.open.../riv/klicoveSlovo	Multi-level vector quantization OpenCL decompression BTF bidirectional texture function GPU
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	JC
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	1 (xsd:int)
http://linked.open...vavai/riv/projekt	Optimal Algorithms for Image Synthesis
http://linked.open...UplatneniVysledku	2013
http://linked.open...iv/tvurceVysledku	Egert, Petr
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2013-04-28 (xsd:date)
number of pages	8 (xsd:int)
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

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 105 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software