Title
Improved Pressure Sensitive Paint Measurement Using Natural Feature Tracking and Piecewise Linear Resection
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.
Year
DOI
Venue
2011
10.1109/CRV.2011.14
Computer and Robot Vision
Keywords
Field
DocType
physical wind tunnel model,wind tunnel imagery,wind tunnel pressure sensitive,nonlinear deformation,accurate registration,increased tracking point coverage,wind-off camera image pair,improved pressure,natural feature tracking,deformation error,piecewise linear resection,pre-defined deformation equation,automatic plr,sensitive paint measurement,resection,visualization,feature extraction,tracking,computer vision,deformation,pressure measurement,wind tunnels,piecewise linear,mathematical model,wind tunnel,image registration,solid modeling
Pressure-sensitive paint,Computer vision,Fiducial marker,Computer science,Pressure measurement,Filter (signal processing),Feature extraction,Artificial intelligence,Wind tunnel,Piecewise linear function,Image registration
Conference
ISBN
Citations 
PageRank 
978-0-7695-4362-8
0
0.34
References 
Authors
1
3
Name
Order
Citations
PageRank
Jeremy Kuzub101.01
Youssef Mebarki200.34
Anthony Whitehead314320.84