A functional error analysis of differential optical flow methods
We analyze the sources of error in differential optical flow methods using techniques for the analysis of partial differential equations. We first derive an a priori error bound for the estimated optical flow field. We then systematically interpret this error bound and show that the estimation error...
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Veröffentlicht in: | Experiments in fluids 2021-08, Vol.62 (8), Article 159 |
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creator | Kumashiro, Keishi Steinberg, Adam M. Yano, Masayuki |
description | We analyze the sources of error in differential optical flow methods using techniques for the analysis of partial differential equations. We first derive an a priori error bound for the estimated optical flow field. We then systematically interpret this error bound and show that the estimation error is primarily bounded by the
best-fit approximation error
—which quantifies the fidelity with which one can represent the true optical flow field by a chosen or learned set of basis functions—divided by a
stability constant
—which quantifies one’s ability to infer the optical flow field given the information content of the acquired data. We also show that the estimation error is bounded by effects associated with the finite temporal and spatial resolution of the acquired data. In particular, we show that the main finite resolution effects are related to the finite differencing and time averaging of the measured intensity fields. Finally, we demonstrate the error bound numerically using synthetic three-dimensional data sets based on direct numerical simulations of homogeneous isotropic turbulence and transitional boundary layer flow provided by Johns Hopkins University (Li et al. in J Turbul 9:N31, 2008; Zaki in Flow Turbul Combust in 91(3):451–473, 2013).
Graphic abstract |
doi_str_mv | 10.1007/s00348-021-03244-1 |
format | Article |
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best-fit approximation error
—which quantifies the fidelity with which one can represent the true optical flow field by a chosen or learned set of basis functions—divided by a
stability constant
—which quantifies one’s ability to infer the optical flow field given the information content of the acquired data. We also show that the estimation error is bounded by effects associated with the finite temporal and spatial resolution of the acquired data. In particular, we show that the main finite resolution effects are related to the finite differencing and time averaging of the measured intensity fields. Finally, we demonstrate the error bound numerically using synthetic three-dimensional data sets based on direct numerical simulations of homogeneous isotropic turbulence and transitional boundary layer flow provided by Johns Hopkins University (Li et al. in J Turbul 9:N31, 2008; Zaki in Flow Turbul Combust in 91(3):451–473, 2013).
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best-fit approximation error
—which quantifies the fidelity with which one can represent the true optical flow field by a chosen or learned set of basis functions—divided by a
stability constant
—which quantifies one’s ability to infer the optical flow field given the information content of the acquired data. We also show that the estimation error is bounded by effects associated with the finite temporal and spatial resolution of the acquired data. In particular, we show that the main finite resolution effects are related to the finite differencing and time averaging of the measured intensity fields. Finally, we demonstrate the error bound numerically using synthetic three-dimensional data sets based on direct numerical simulations of homogeneous isotropic turbulence and transitional boundary layer flow provided by Johns Hopkins University (Li et al. in J Turbul 9:N31, 2008; Zaki in Flow Turbul Combust in 91(3):451–473, 2013).
Graphic abstract</description><subject>Basis functions</subject><subject>Boundary layer flow</subject><subject>Boundary layer transition</subject><subject>Computational fluid dynamics</subject><subject>Data acquisition</subject><subject>Direct numerical simulation</subject><subject>Engineering</subject><subject>Engineering Fluid Dynamics</subject><subject>Engineering Thermodynamics</subject><subject>Error analysis</subject><subject>Flow stability</subject><subject>Fluid- and Aerodynamics</subject><subject>Heat and Mass Transfer</subject><subject>Isotropic turbulence</subject><subject>Mathematical analysis</subject><subject>Optical flow (image analysis)</subject><subject>Partial differential equations</subject><subject>Pedestrians</subject><subject>Research Article</subject><subject>Spatial resolution</subject><issn>0723-4864</issn><issn>1432-1114</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kE9LxDAUxIMoWFe_gKeC5-h7SZo0N5fFf7DgZe8h7SbapdvUpIvstzdawZunefBmhuFHyDXCLQKouwTARU2BIQXOhKB4QgoUnFFEFKekAMU4FbUU5-QipR0AVhrqgtwvS38Y2qkLg-1LF2OIpc3nMXWpDL7cdt676Iapy-8wTl2b1ffhs9y76T1s0yU587ZP7upXF2Tz-LBZPdP169PLarmmLUc90Ro0A-Yr59HWDJTyFefgFHLZSPCNarSSjnG0XskGtKpa8LW2eTe0oPmC3My1YwwfB5cmswuHmIcmw6oKpFRcy-xis6uNIaXovBljt7fxaBDMNygzgzIZlPkBZTCH-BxK2Ty8ufhX_U_qC8rdab4</recordid><startdate>20210801</startdate><enddate>20210801</enddate><creator>Kumashiro, Keishi</creator><creator>Steinberg, Adam M.</creator><creator>Yano, Masayuki</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-3456-7577</orcidid></search><sort><creationdate>20210801</creationdate><title>A functional error analysis of differential optical flow methods</title><author>Kumashiro, Keishi ; Steinberg, Adam M. ; Yano, Masayuki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-809202f5ef1a82077f5330e7136b60fb7b976e231af76b0975c0f89a0720c093</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Basis functions</topic><topic>Boundary layer flow</topic><topic>Boundary layer transition</topic><topic>Computational fluid dynamics</topic><topic>Data acquisition</topic><topic>Direct numerical simulation</topic><topic>Engineering</topic><topic>Engineering Fluid Dynamics</topic><topic>Engineering Thermodynamics</topic><topic>Error analysis</topic><topic>Flow stability</topic><topic>Fluid- and Aerodynamics</topic><topic>Heat and Mass Transfer</topic><topic>Isotropic turbulence</topic><topic>Mathematical analysis</topic><topic>Optical flow (image analysis)</topic><topic>Partial differential equations</topic><topic>Pedestrians</topic><topic>Research Article</topic><topic>Spatial resolution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kumashiro, Keishi</creatorcontrib><creatorcontrib>Steinberg, Adam M.</creatorcontrib><creatorcontrib>Yano, Masayuki</creatorcontrib><collection>CrossRef</collection><jtitle>Experiments in fluids</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kumashiro, Keishi</au><au>Steinberg, Adam M.</au><au>Yano, Masayuki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A functional error analysis of differential optical flow methods</atitle><jtitle>Experiments in fluids</jtitle><stitle>Exp Fluids</stitle><date>2021-08-01</date><risdate>2021</risdate><volume>62</volume><issue>8</issue><artnum>159</artnum><issn>0723-4864</issn><eissn>1432-1114</eissn><abstract>We analyze the sources of error in differential optical flow methods using techniques for the analysis of partial differential equations. We first derive an a priori error bound for the estimated optical flow field. We then systematically interpret this error bound and show that the estimation error is primarily bounded by the
best-fit approximation error
—which quantifies the fidelity with which one can represent the true optical flow field by a chosen or learned set of basis functions—divided by a
stability constant
—which quantifies one’s ability to infer the optical flow field given the information content of the acquired data. We also show that the estimation error is bounded by effects associated with the finite temporal and spatial resolution of the acquired data. In particular, we show that the main finite resolution effects are related to the finite differencing and time averaging of the measured intensity fields. Finally, we demonstrate the error bound numerically using synthetic three-dimensional data sets based on direct numerical simulations of homogeneous isotropic turbulence and transitional boundary layer flow provided by Johns Hopkins University (Li et al. in J Turbul 9:N31, 2008; Zaki in Flow Turbul Combust in 91(3):451–473, 2013).
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subjects | Basis functions Boundary layer flow Boundary layer transition Computational fluid dynamics Data acquisition Direct numerical simulation Engineering Engineering Fluid Dynamics Engineering Thermodynamics Error analysis Flow stability Fluid- and Aerodynamics Heat and Mass Transfer Isotropic turbulence Mathematical analysis Optical flow (image analysis) Partial differential equations Pedestrians Research Article Spatial resolution |
title | A functional error analysis of differential optical flow methods |
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