Scale and rotation invariant detection of singular patterns in vector flow fields

Authors:
Wei Liu;Eraldo Ribeiro
Affiliations:
Computer Vision and Bio-Inspired Computing Laboratory, Department of Computer Sciences, Florida Institute of Technology, Melbourne, FL;Computer Vision and Bio-Inspired Computing Laboratory, Department of Computer Sciences, Florida Institute of Technology, Melbourne, FL
Venue:
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Year:
2010

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Abstract

We present a method for detecting and describing features in vector flow fields. Our method models flow fields locally using a linear combination of complex monomials. These monomials form an orthogonal basis for analytic flows with respect to a correlation-based innerproduct. We investigate the invariance properties of the coefficients of the approximation polynomials under both rotation and scaling operators. We then propose a descriptor for local flow patterns, and developed a method for comparing them invariantly against rigid transformations. Additionally, we propose a SIFT-like detector that can automatically detect singular flow patterns at different scales and orientations. Promising detection results are obtained on different fluid flow data.