This article describes a F0 curve estimation scheme based on a B-spline model1. We compare this model with more classical spline representation. The free parameters of both models are the number of knots and their location. An optimal location is proposed using a simulated annealing strategy. Experiments on real F0 curves confirm the adequacy and good performance of the B-spline approach, estim...

We propose a method of analyzing collections of related curves in which the individual curves are modeled as spline functions with random coefficients. The method is applicable when the individual curves are sampled at variable and irregularly spaced points. This produces a low-rank, low-frequency approximation to the covariance structure, which can be estimated naturally by the EM algorithm. S...

Interpolating splines are a basic primitive for designing planar curves. There is a wide diversity in the literature but no consensus on a ―best‖ spline, or even criteria for preferring one spline over another. For the case of G-continuous splines, we emphasize two properties that can arguably be expected in any definition of ―best‖ and show that any such spline is made from segments cut from a...

In this study the problem of modeling a family of curves is addressed. The need of such modeling appears frequently in many aspects of image processing where many linear structures keep spatial relationships during their evolution. We come up with a modeling tool well suited to the spatial modeling of a family of curves, and which can be very useful for motion tracking and curve evolution as we...

This short paper describes our three submissions to the 2014 edition of the MIREX Symbolic Melodic Similarity task. All three submissions rely on a geometric model that represents melodies as spline curves in the pitch-time plane. The similarity between two melodies is then computed with a sequence alignment algorithm between sequences of spline spans: the more similar the shape of the curves, ...

We adapt the interactive spline model of Wahba to growth curves with covariates. The smoothing spline formulation permits a nonparametric representation of the growth curves. In the limit when the discretization error is small relative to the estimation error, the resulting growth curve estimates often depend only weakly on the number and locations of the knots. The smoothness parameter is dete...