Detecting singular patterns in 2D vector fields using weighted Laurent polynomial

Authors:
Wei Liu;Eraldo Ribeiro
Affiliations:
Computer Vision Laboratory, Department of Computer Sciences, Florida Institute of Technology, Melbourne, FL 32901, USA;Computer Vision Laboratory, Department of Computer Sciences, Florida Institute of Technology, Melbourne, FL 32901, USA
Venue:
Pattern Recognition
Year:
2012

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Abstract

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.