Contour analysis using time-varying autoregressive model
Kie Bum Eom · 2000
Contour modeling by a time-varying autoregressive (TVAR) model is considered. A least squares estimator of the TVAR model parameters is presented, and the maximum likelihood approach for determining the model order is also presented. In the experiment, curvature extrema points of synthesized contours are detected from the time frequency distribution estimated with TVAR model. In the classification experiment with contours of various planar shapes, about 97% of samples are correctly classified.