DocumentCode
2342165
Title
Improved Pressure Sensitive Paint Measurement Using Natural Feature Tracking and Piecewise Linear Resection
Author
Kuzub, Jeremy ; Mebarki, Youssef ; Whitehead, Anthony
Author_Institution
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
fYear
2011
fDate
25-27 May 2011
Firstpage
48
Lastpage
55
Abstract
Wind tunnel Pressure Sensitive Paint (PSP) ratio techniques require accurate registration between wind-on and wind-off camera image pairs. The Piecewise Linear Resection (PLR) method of removing registration due to physical wind tunnel model motion and deformation errors can account for nonlinear deformations and benefits from increased tracking point coverage in the image. This work presents a method to increase the accuracy of PLR by tracking natural features in addition to standard fiducial markers. This is accomplished with Speeded-Up Robust Features (SURF) and a modified disparity gradient filtering technique. This work shows that this method of automatic PLR is feasible on wind tunnel imagery and that the resulting pressure data has reduced mis-registration noise without the need to perform 3D resection using virtual models and pre-defined deformation equations.
Keywords
filtering theory; gradient methods; image registration; pressure measurement; wind tunnels; PLR; deformation errors; disparity gradient filtering technique; natural feature tracking; physical wind tunnel model motion; piecewise linear resection; speeded-up robust features; wind tunnel imagery; wind tunnel pressure sensitive paint ratio techniques; Cameras; Deformable models; Feature extraction; Mathematical model; Solid modeling; Three dimensional displays; Tracking; computer vision; deformation; misregistration; pressure sensitive paint; resection; visualization; wind tunnel;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Robot Vision (CRV), 2011 Canadian Conference on
Conference_Location
St. Johns, NL
Print_ISBN
978-1-61284-430-5
Electronic_ISBN
978-0-7695-4362-8
Type
conf
DOI
10.1109/CRV.2011.14
Filename
5957541
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