A model based algorithm for fast DPIV computing

Abstract Traditional DPIV (Digital Particle Image Velocimetry) methods are mostly based on area-correlation (Willert, C. E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also beca...
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Autor*in:	Tian-ding, Chen [verfasserIn] Hong-dong, Li Ji-lin, Liu Wei-kang, Gu

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2001

Anmerkung:	© Zhejiang University Press 2001

Übergeordnetes Werk:	Enthalten in: Journal of Zhejiang University - Hangzhou : Zhejiang University Press, 2005, 2(2001), 1 vom: 01. Jan., Seite 46-50
Übergeordnetes Werk:	volume:2 ; year:2001 ; number:1 ; day:01 ; month:01 ; pages:46-50

Links:	Volltext

DOI / URN:	10.1007/BF02841175

Katalog-ID:	SPR020879504

Internformat


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245	1	2	\|a A model based algorithm for fast DPIV computing
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520			\|a Abstract Traditional DPIV (Digital Particle Image Velocimetry) methods are mostly based on area-correlation (Willert, C. E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also because there are few alternatives. This paper proposes a non-correlation, conceptually new, fast and efficient approach for DPIV, which takes the nature of flow into consideration. An Incompressible Affined Flow Model (IAFM) is introduced to describe a flow that incorporates rational restraints into the computation. This IAFM, combined with a modified optical flow method-named Total Optical Flow Computation (TOFC), provides a linear system solution to DPIV. Experimental results on real images showed our method to be a very promising approach for DPIV.
700	1		\|a Hong-dong, Li \|4 aut
700	1		\|a Ji-lin, Liu \|4 aut
700	1		\|a Wei-kang, Gu \|4 aut
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912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_120
912			\|a GBV_ILN_138
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_152
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2107
912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2116
912			\|a GBV_ILN_2118
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912			\|a GBV_ILN_2144
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912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2188
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2446
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2472
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_2548
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4046
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4246
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4336
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
912			\|a GBV_ILN_4700
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952			\|d 2 \|j 2001 \|e 1 \|b 01 \|c 01 \|h 46-50

Indexfelder

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publishDate	2001
allfields	10.1007/BF02841175 doi (DE-627)SPR020879504 (SPR)BF02841175-e DE-627 ger DE-627 rakwb eng Tian-ding, Chen verfasserin aut A model based algorithm for fast DPIV computing 2001 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Zhejiang University Press 2001 Abstract Traditional DPIV (Digital Particle Image Velocimetry) methods are mostly based on area-correlation (Willert, C. E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also because there are few alternatives. This paper proposes a non-correlation, conceptually new, fast and efficient approach for DPIV, which takes the nature of flow into consideration. An Incompressible Affined Flow Model (IAFM) is introduced to describe a flow that incorporates rational restraints into the computation. This IAFM, combined with a modified optical flow method-named Total Optical Flow Computation (TOFC), provides a linear system solution to DPIV. Experimental results on real images showed our method to be a very promising approach for DPIV. Hong-dong, Li aut Ji-lin, Liu aut Wei-kang, Gu aut Enthalten in Journal of Zhejiang University Hangzhou : Zhejiang University Press, 2005 2(2001), 1 vom: 01. Jan., Seite 46-50 (DE-627)52019568X (DE-600)2257662-9 1862-1775 nnns volume:2 year:2001 number:1 day:01 month:01 pages:46-50 https://dx.doi.org/10.1007/BF02841175 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 2 2001 1 01 01 46-50
spelling	10.1007/BF02841175 doi (DE-627)SPR020879504 (SPR)BF02841175-e DE-627 ger DE-627 rakwb eng Tian-ding, Chen verfasserin aut A model based algorithm for fast DPIV computing 2001 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Zhejiang University Press 2001 Abstract Traditional DPIV (Digital Particle Image Velocimetry) methods are mostly based on area-correlation (Willert, C. E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also because there are few alternatives. This paper proposes a non-correlation, conceptually new, fast and efficient approach for DPIV, which takes the nature of flow into consideration. An Incompressible Affined Flow Model (IAFM) is introduced to describe a flow that incorporates rational restraints into the computation. This IAFM, combined with a modified optical flow method-named Total Optical Flow Computation (TOFC), provides a linear system solution to DPIV. Experimental results on real images showed our method to be a very promising approach for DPIV. Hong-dong, Li aut Ji-lin, Liu aut Wei-kang, Gu aut Enthalten in Journal of Zhejiang University Hangzhou : Zhejiang University Press, 2005 2(2001), 1 vom: 01. Jan., Seite 46-50 (DE-627)52019568X (DE-600)2257662-9 1862-1775 nnns volume:2 year:2001 number:1 day:01 month:01 pages:46-50 https://dx.doi.org/10.1007/BF02841175 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 2 2001 1 01 01 46-50
allfields_unstemmed	10.1007/BF02841175 doi (DE-627)SPR020879504 (SPR)BF02841175-e DE-627 ger DE-627 rakwb eng Tian-ding, Chen verfasserin aut A model based algorithm for fast DPIV computing 2001 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Zhejiang University Press 2001 Abstract Traditional DPIV (Digital Particle Image Velocimetry) methods are mostly based on area-correlation (Willert, C. E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also because there are few alternatives. This paper proposes a non-correlation, conceptually new, fast and efficient approach for DPIV, which takes the nature of flow into consideration. An Incompressible Affined Flow Model (IAFM) is introduced to describe a flow that incorporates rational restraints into the computation. This IAFM, combined with a modified optical flow method-named Total Optical Flow Computation (TOFC), provides a linear system solution to DPIV. Experimental results on real images showed our method to be a very promising approach for DPIV. Hong-dong, Li aut Ji-lin, Liu aut Wei-kang, Gu aut Enthalten in Journal of Zhejiang University Hangzhou : Zhejiang University Press, 2005 2(2001), 1 vom: 01. Jan., Seite 46-50 (DE-627)52019568X (DE-600)2257662-9 1862-1775 nnns volume:2 year:2001 number:1 day:01 month:01 pages:46-50 https://dx.doi.org/10.1007/BF02841175 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 2 2001 1 01 01 46-50
allfieldsGer	10.1007/BF02841175 doi (DE-627)SPR020879504 (SPR)BF02841175-e DE-627 ger DE-627 rakwb eng Tian-ding, Chen verfasserin aut A model based algorithm for fast DPIV computing 2001 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Zhejiang University Press 2001 Abstract Traditional DPIV (Digital Particle Image Velocimetry) methods are mostly based on area-correlation (Willert, C. E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also because there are few alternatives. This paper proposes a non-correlation, conceptually new, fast and efficient approach for DPIV, which takes the nature of flow into consideration. An Incompressible Affined Flow Model (IAFM) is introduced to describe a flow that incorporates rational restraints into the computation. This IAFM, combined with a modified optical flow method-named Total Optical Flow Computation (TOFC), provides a linear system solution to DPIV. Experimental results on real images showed our method to be a very promising approach for DPIV. Hong-dong, Li aut Ji-lin, Liu aut Wei-kang, Gu aut Enthalten in Journal of Zhejiang University Hangzhou : Zhejiang University Press, 2005 2(2001), 1 vom: 01. Jan., Seite 46-50 (DE-627)52019568X (DE-600)2257662-9 1862-1775 nnns volume:2 year:2001 number:1 day:01 month:01 pages:46-50 https://dx.doi.org/10.1007/BF02841175 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 2 2001 1 01 01 46-50
allfieldsSound	10.1007/BF02841175 doi (DE-627)SPR020879504 (SPR)BF02841175-e DE-627 ger DE-627 rakwb eng Tian-ding, Chen verfasserin aut A model based algorithm for fast DPIV computing 2001 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Zhejiang University Press 2001 Abstract Traditional DPIV (Digital Particle Image Velocimetry) methods are mostly based on area-correlation (Willert, C. E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also because there are few alternatives. This paper proposes a non-correlation, conceptually new, fast and efficient approach for DPIV, which takes the nature of flow into consideration. An Incompressible Affined Flow Model (IAFM) is introduced to describe a flow that incorporates rational restraints into the computation. This IAFM, combined with a modified optical flow method-named Total Optical Flow Computation (TOFC), provides a linear system solution to DPIV. Experimental results on real images showed our method to be a very promising approach for DPIV. Hong-dong, Li aut Ji-lin, Liu aut Wei-kang, Gu aut Enthalten in Journal of Zhejiang University Hangzhou : Zhejiang University Press, 2005 2(2001), 1 vom: 01. Jan., Seite 46-50 (DE-627)52019568X (DE-600)2257662-9 1862-1775 nnns volume:2 year:2001 number:1 day:01 month:01 pages:46-50 https://dx.doi.org/10.1007/BF02841175 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 2 2001 1 01 01 46-50
language	English
source	Enthalten in Journal of Zhejiang University 2(2001), 1 vom: 01. Jan., Seite 46-50 volume:2 year:2001 number:1 day:01 month:01 pages:46-50
sourceStr	Enthalten in Journal of Zhejiang University 2(2001), 1 vom: 01. Jan., Seite 46-50 volume:2 year:2001 number:1 day:01 month:01 pages:46-50
format_phy_str_mv	Article
institution	findex.gbv.de
isfreeaccess_bool	false
container_title	Journal of Zhejiang University
authorswithroles_txt_mv	Tian-ding, Chen @@aut@@ Hong-dong, Li @@aut@@ Ji-lin, Liu @@aut@@ Wei-kang, Gu @@aut@@
publishDateDaySort_date	2001-01-01T00:00:00Z
hierarchy_top_id	52019568X
id	SPR020879504
language_de	englisch
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author	Tian-ding, Chen
spellingShingle	Tian-ding, Chen A model based algorithm for fast DPIV computing
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topic_title	A model based algorithm for fast DPIV computing
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title	A model based algorithm for fast DPIV computing
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title_full	A model based algorithm for fast DPIV computing
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author_browse	Tian-ding, Chen Hong-dong, Li Ji-lin, Liu Wei-kang, Gu
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author-letter	Tian-ding, Chen
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title_sort	model based algorithm for fast dpiv computing
title_auth	A model based algorithm for fast DPIV computing
abstract	Abstract Traditional DPIV (Digital Particle Image Velocimetry) methods are mostly based on area-correlation (Willert, C. E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also because there are few alternatives. This paper proposes a non-correlation, conceptually new, fast and efficient approach for DPIV, which takes the nature of flow into consideration. An Incompressible Affined Flow Model (IAFM) is introduced to describe a flow that incorporates rational restraints into the computation. This IAFM, combined with a modified optical flow method-named Total Optical Flow Computation (TOFC), provides a linear system solution to DPIV. Experimental results on real images showed our method to be a very promising approach for DPIV. © Zhejiang University Press 2001
abstractGer	Abstract Traditional DPIV (Digital Particle Image Velocimetry) methods are mostly based on area-correlation (Willert, C. E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also because there are few alternatives. This paper proposes a non-correlation, conceptually new, fast and efficient approach for DPIV, which takes the nature of flow into consideration. An Incompressible Affined Flow Model (IAFM) is introduced to describe a flow that incorporates rational restraints into the computation. This IAFM, combined with a modified optical flow method-named Total Optical Flow Computation (TOFC), provides a linear system solution to DPIV. Experimental results on real images showed our method to be a very promising approach for DPIV. © Zhejiang University Press 2001
abstract_unstemmed	Abstract Traditional DPIV (Digital Particle Image Velocimetry) methods are mostly based on area-correlation (Willert, C. E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also because there are few alternatives. This paper proposes a non-correlation, conceptually new, fast and efficient approach for DPIV, which takes the nature of flow into consideration. An Incompressible Affined Flow Model (IAFM) is introduced to describe a flow that incorporates rational restraints into the computation. This IAFM, combined with a modified optical flow method-named Total Optical Flow Computation (TOFC), provides a linear system solution to DPIV. Experimental results on real images showed our method to be a very promising approach for DPIV. © Zhejiang University Press 2001
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title_short	A model based algorithm for fast DPIV computing
url	https://dx.doi.org/10.1007/BF02841175
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author2	Hong-dong, Li Ji-lin, Liu Wei-kang, Gu
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up_date	2024-07-03T18:51:39.353Z
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E., 1991). Though proven to be very time-consuming and very much error prone, they are widely adopted because of they are conceptually simple and easily implemented, and also because there are few alternatives. This paper proposes a non-correlation, conceptually new, fast and efficient approach for DPIV, which takes the nature of flow into consideration. An Incompressible Affined Flow Model (IAFM) is introduced to describe a flow that incorporates rational restraints into the computation. This IAFM, combined with a modified optical flow method-named Total Optical Flow Computation (TOFC), provides a linear system solution to DPIV. 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A model based algorithm for fast DPIV computing

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