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Detecting singular patterns in 2D vector fields using weighted Laurent polynomial
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DOI：10.1016/j.patcog.2012.04.025.png)
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Abstract
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In this paper, we propose a method for detecting patterns of interest in vector fields. Our method detects patterns in a scale- and rotation-invariant manner. It works by approximating the vector-field data locally using a Laurent polynomial weighted by radial basis functions. The proposed representation is able to model both analytic and non-analytic flow fields. Invariance to scale and rotation is achieved by combining the linearity properties of the model coefficients and a scale-space parameter of the radial basis functions. Promising detection results are obtained on a variety of fluid-flow sequences. (C) 2012 Elsevier Ltd. All rights reserved.
Keywords:
Vector fields
Singular-pattern detection
Scale- and rotation-invariance
Complex-valued function
Laurent polynomials
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