Fast and accurate PIV computation using highly parallel iterative correlation maximization
Identifieur interne :
001B41 ( PascalFrancis/Corpus );
précédent :
001B40;
suivant :
001B42
Fast and accurate PIV computation using highly parallel iterative correlation maximization
Auteurs : F. Champagnat ;
A. Plyer ;
G. Le Besnerais ;
B. Leclaire ;
S. Davoust ;
Y. Le SantSource :
-
Experiments in fluids [ 0723-4864 ] ; 2011.
RBID : Pascal:11-0305222
Descripteurs français
English descriptors
Abstract
Our contribution deals with fast computation of dense two-component (2C) PIV vector fields using Graphics Processing Units (GPUs). We show that iterative gradient-based cross-correlation optimization is an accurate and efficient alternative to multi-pass processing with FFT-based cross-correlation. Density is meant here from the sampling point of view (we obtain one vector per pixel), since the presented algorithm, FOLKI, naturally performs fast correlation optimization over interrogation windows with maximal overlap. The processing of 5 image pairs (1,376 x 1,040 each) is achieved in less than a second on a NVIDIA Tesla C1060 GPU. Various tests on synthetic and experimental images, including a dataset of the 2nd PIV challenge, show that the accuracy of FOLKI is found comparable to that of state-of-the-art FFT-based commercial softwares, while being 50 times faster.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
| pA |
| A01 | 01 | 1 | | @0 0723-4864 |
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| A02 | 01 | | | @0 EXFLDU |
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| A03 | | 1 | | @0 Exp. fluids |
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| A05 | | | | @2 50 |
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| A06 | | | | @2 4 |
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| A08 | 01 | 1 | ENG | @1 Fast and accurate PIV computation using highly parallel iterative correlation maximization |
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| A09 | 01 | 1 | ENG | @1 Eighth International Symposium on Particle Image Velocimetry (PIV'09) |
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| A11 | 01 | 1 | | @1 CHAMPAGNAT (F.) |
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| A11 | 02 | 1 | | @1 PLYER (A.) |
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| A11 | 03 | 1 | | @1 LE BESNERAIS (G.) |
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| A11 | 04 | 1 | | @1 LECLAIRE (B.) |
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| A11 | 05 | 1 | | @1 DAVOUST (S.) |
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| A11 | 06 | 1 | | @1 LE SANT (Y.) |
|---|
| A12 | 01 | 1 | | @1 SORIA (Julio) @9 ed. |
|---|
| A12 | 02 | 1 | | @1 CLEMENS (Noel T.) @9 ed. |
|---|
| A14 | 01 | | | @1 Modeling and Information Processing Department, French Aerospace Lab (ONERA), Chemin de la Hunière @2 91761 Palaiseau @3 FRA @Z 1 aut. @Z 2 aut. @Z 3 aut. |
|---|
| A14 | 02 | | | @1 Fundamental and Experimental Aerodynamics Department, French Aerospace Lab (ONERA), 8 rue des Vertugadins @2 92190 Meudon @3 FRA @Z 4 aut. @Z 5 aut. @Z 6 aut. |
|---|
| A15 | 01 | | | @1 Laboratory for Turbulence Research in Aerospace and Combustion, Department of Mechanical and Aerospace Engineering, Monash University, Clayton Campus @2 Melbourne, VIC 3800 @3 AUS @Z 1 aut. |
|---|
| A15 | 02 | | | @1 Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, 1 University Station C0600 @2 Austin, TX 78712 @3 USA @Z 2 aut. |
|---|
| A18 | 01 | 1 | | @1 Monash University @2 Victoria @3 AUS @9 org-cong. |
|---|
| A20 | | | | @1 1169-1182 |
|---|
| A21 | | | | @1 2011 |
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| A23 | 01 | | | @0 ENG |
|---|
| A43 | 01 | | | @1 INIST @2 19904 @5 354000192957660280 |
|---|
| A44 | | | | @0 0000 @1 © 2011 INIST-CNRS. All rights reserved. |
|---|
| A45 | | | | @0 3/4 p. |
|---|
| A47 | 01 | 1 | | @0 11-0305222 |
|---|
| A60 | | | | @1 P @2 C |
|---|
| A61 | | | | @0 A |
|---|
| A64 | 01 | 1 | | @0 Experiments in fluids |
|---|
| A66 | 01 | | | @0 DEU |
|---|
| C01 | 01 | | ENG | @0 Our contribution deals with fast computation of dense two-component (2C) PIV vector fields using Graphics Processing Units (GPUs). We show that iterative gradient-based cross-correlation optimization is an accurate and efficient alternative to multi-pass processing with FFT-based cross-correlation. Density is meant here from the sampling point of view (we obtain one vector per pixel), since the presented algorithm, FOLKI, naturally performs fast correlation optimization over interrogation windows with maximal overlap. The processing of 5 image pairs (1,376 x 1,040 each) is achieved in less than a second on a NVIDIA Tesla C1060 GPU. Various tests on synthetic and experimental images, including a dataset of the 2nd PIV challenge, show that the accuracy of FOLKI is found comparable to that of state-of-the-art FFT-based commercial softwares, while being 50 times faster. |
|---|
| C02 | 01 | 3 | | @0 001B40G80 |
|---|
| C03 | 01 | 3 | FRE | @0 Performance @5 08 |
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| C03 | 01 | 3 | ENG | @0 Performance @5 08 |
|---|
| C03 | 02 | 3 | FRE | @0 Champ vectoriel @5 09 |
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| C03 | 02 | 3 | ENG | @0 Vector fields @5 09 |
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| C03 | 03 | 3 | FRE | @0 Algorithme @5 12 |
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| C03 | 03 | 3 | ENG | @0 Algorithms @5 12 |
|---|
| C03 | 04 | 3 | FRE | @0 Méthode itérative @5 13 |
|---|
| C03 | 04 | 3 | ENG | @0 Iterative methods @5 13 |
|---|
| C03 | 05 | 3 | FRE | @0 Vélocimétrie image particule @5 17 |
|---|
| C03 | 05 | 3 | ENG | @0 Particle image velocimetry @5 17 |
|---|
| C03 | 06 | 3 | FRE | @0 Mesure vitesse @5 18 |
|---|
| C03 | 06 | 3 | ENG | @0 Velocity measurement @5 18 |
|---|
| C03 | 07 | 3 | FRE | @0 Réponse fréquence @5 29 |
|---|
| C03 | 07 | 3 | ENG | @0 Frequency response @5 29 |
|---|
| C03 | 08 | 3 | FRE | @0 Traitement image @5 30 |
|---|
| C03 | 08 | 3 | ENG | @0 Image processing @5 30 |
|---|
| C03 | 09 | 3 | FRE | @0 4780 @4 INC @5 56 |
|---|
| N21 | | | | @1 206 |
|---|
|
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| pR |
| A30 | 01 | 1 | ENG | @1 International Symposium on Particle Image Velocimetry (PIV'09) @3 Melbourne AUS @4 2009-08-25 |
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|
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Format Inist (serveur)
| NO : | PASCAL 11-0305222 INIST |
|---|
| ET : | Fast and accurate PIV computation using highly parallel iterative correlation maximization |
|---|
| AU : | CHAMPAGNAT (F.); PLYER (A.); LE BESNERAIS (G.); LECLAIRE (B.); DAVOUST (S.); LE SANT (Y.); SORIA (Julio); CLEMENS (Noel T.) |
|---|
| AF : | Modeling and Information Processing Department, French Aerospace Lab (ONERA), Chemin de la Hunière/91761 Palaiseau/France (1 aut., 2 aut., 3 aut.); Fundamental and Experimental Aerodynamics Department, French Aerospace Lab (ONERA), 8 rue des Vertugadins/92190 Meudon/France (4 aut., 5 aut., 6 aut.); Laboratory for Turbulence Research in Aerospace and Combustion, Department of Mechanical and Aerospace Engineering, Monash University, Clayton Campus/Melbourne, VIC 3800/Australie (1 aut.); Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, 1 University Station C0600/Austin, TX 78712/Etats-Unis (2 aut.) |
|---|
| DT : | Publication en série; Congrès; Niveau analytique |
|---|
| SO : | Experiments in fluids; ISSN 0723-4864; Coden EXFLDU; Allemagne; Da. 2011; Vol. 50; No. 4; Pp. 1169-1182; Bibl. 3/4 p. |
|---|
| LA : | Anglais |
|---|
| EA : | Our contribution deals with fast computation of dense two-component (2C) PIV vector fields using Graphics Processing Units (GPUs). We show that iterative gradient-based cross-correlation optimization is an accurate and efficient alternative to multi-pass processing with FFT-based cross-correlation. Density is meant here from the sampling point of view (we obtain one vector per pixel), since the presented algorithm, FOLKI, naturally performs fast correlation optimization over interrogation windows with maximal overlap. The processing of 5 image pairs (1,376 x 1,040 each) is achieved in less than a second on a NVIDIA Tesla C1060 GPU. Various tests on synthetic and experimental images, including a dataset of the 2nd PIV challenge, show that the accuracy of FOLKI is found comparable to that of state-of-the-art FFT-based commercial softwares, while being 50 times faster. |
|---|
| CC : | 001B40G80 |
|---|
| FD : | Performance; Champ vectoriel; Algorithme; Méthode itérative; Vélocimétrie image particule; Mesure vitesse; Réponse fréquence; Traitement image; 4780 |
|---|
| ED : | Performance; Vector fields; Algorithms; Iterative methods; Particle image velocimetry; Velocity measurement; Frequency response; Image processing |
|---|
| LO : | INIST-19904.354000192957660280 |
|---|
| ID : | 11-0305222 |
|---|
Links to Exploration step
Pascal:11-0305222
Le document en format XML
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<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
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</inist:fA14><series><title level="j" type="main">Experiments in fluids</title>
<title level="j" type="abbreviated">Exp. fluids</title>
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<imprint><date when="2011">2011</date>
</imprint><seriesStmt><title level="j" type="main">Experiments in fluids</title>
<title level="j" type="abbreviated">Exp. fluids</title>
<idno type="ISSN">0723-4864</idno>
</seriesStmt><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term>
<term>Frequency response</term>
<term>Image processing</term>
<term>Iterative methods</term>
<term>Particle image velocimetry</term>
<term>Performance</term>
<term>Vector fields</term>
<term>Velocity measurement</term>
</keywords><keywords scheme="Pascal" xml:lang="fr"><term>Performance</term>
<term>Champ vectoriel</term>
<term>Algorithme</term>
<term>Méthode itérative</term>
<term>Vélocimétrie image particule</term>
<term>Mesure vitesse</term>
<term>Réponse fréquence</term>
<term>Traitement image</term>
<term>4780</term>
</keywords><front><div type="abstract" xml:lang="en">Our contribution deals with fast computation of dense two-component (2C) PIV vector fields using Graphics Processing Units (GPUs). We show that iterative gradient-based cross-correlation optimization is an accurate and efficient alternative to multi-pass processing with FFT-based cross-correlation. Density is meant here from the sampling point of view (we obtain one vector per pixel), since the presented algorithm, FOLKI, naturally performs fast correlation optimization over interrogation windows with maximal overlap. The processing of 5 image pairs (1,376 x 1,040 each) is achieved in less than a second on a NVIDIA Tesla C1060 GPU. Various tests on synthetic and experimental images, including a dataset of the 2nd PIV challenge, show that the accuracy of FOLKI is found comparable to that of state-of-the-art FFT-based commercial softwares, while being 50 times faster.</div>
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</fA11><fA11 i1="04" i2="1"><s1>LECLAIRE (B.)</s1>
</fA11><fA11 i1="05" i2="1"><s1>DAVOUST (S.)</s1>
</fA11><fA11 i1="06" i2="1"><s1>LE SANT (Y.)</s1>
</fA11><fA12 i1="01" i2="1"><s1>SORIA (Julio)</s1>
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<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
</fA14><fA14 i1="02"><s1>Fundamental and Experimental Aerodynamics Department, French Aerospace Lab (ONERA), 8 rue des Vertugadins</s1>
<s2>92190 Meudon</s2>
<s3>FRA</s3>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
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<s5>29</s5>
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<ET>Fast and accurate PIV computation using highly parallel iterative correlation maximization</ET>
<AU>CHAMPAGNAT (F.); PLYER (A.); LE BESNERAIS (G.); LECLAIRE (B.); DAVOUST (S.); LE SANT (Y.); SORIA (Julio); CLEMENS (Noel T.)</AU>
<AF>Modeling and Information Processing Department, French Aerospace Lab (ONERA), Chemin de la Hunière/91761 Palaiseau/France (1 aut., 2 aut., 3 aut.); Fundamental and Experimental Aerodynamics Department, French Aerospace Lab (ONERA), 8 rue des Vertugadins/92190 Meudon/France (4 aut., 5 aut., 6 aut.); Laboratory for Turbulence Research in Aerospace and Combustion, Department of Mechanical and Aerospace Engineering, Monash University, Clayton Campus/Melbourne, VIC 3800/Australie (1 aut.); Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, 1 University Station C0600/Austin, TX 78712/Etats-Unis (2 aut.)</AF>
<DT>Publication en série; Congrès; Niveau analytique</DT>
<SO>Experiments in fluids; ISSN 0723-4864; Coden EXFLDU; Allemagne; Da. 2011; Vol. 50; No. 4; Pp. 1169-1182; Bibl. 3/4 p.</SO>
<LA>Anglais</LA>
<EA>Our contribution deals with fast computation of dense two-component (2C) PIV vector fields using Graphics Processing Units (GPUs). We show that iterative gradient-based cross-correlation optimization is an accurate and efficient alternative to multi-pass processing with FFT-based cross-correlation. Density is meant here from the sampling point of view (we obtain one vector per pixel), since the presented algorithm, FOLKI, naturally performs fast correlation optimization over interrogation windows with maximal overlap. The processing of 5 image pairs (1,376 x 1,040 each) is achieved in less than a second on a NVIDIA Tesla C1060 GPU. Various tests on synthetic and experimental images, including a dataset of the 2nd PIV challenge, show that the accuracy of FOLKI is found comparable to that of state-of-the-art FFT-based commercial softwares, while being 50 times faster.</EA>
<CC>001B40G80</CC>
<FD>Performance; Champ vectoriel; Algorithme; Méthode itérative; Vélocimétrie image particule; Mesure vitesse; Réponse fréquence; Traitement image; 4780</FD>
<ED>Performance; Vector fields; Algorithms; Iterative methods; Particle image velocimetry; Velocity measurement; Frequency response; Image processing</ED>
<LO>INIST-19904.354000192957660280</LO>
<ID>11-0305222</ID>
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