This paper presents an effective method of statistical shape representation for automatic face analysis and identification in 3-D. The method combines statistical shape modelling techniques and the non-rigid deformation matching scheme. This work is distinguished by three key contributions. The first is the introduction of a new 3-D shape registration method using hierarchical landmark detectio...

A new class of Smooth Transition Autoregressive models, based on cubic spline type transition functions, has been introduced and subjected to comparison with models based on the traditional logistic transition functions. A very high degree of similarity between the two model classes has been demonstrated. The new class of models can be slightly preferable because of its more simple formal and g...

Generalized additive mixed models are proposed for overdispersed and correlated data, which arise frequently in studies involving clustered, hierarchical and spatial designs. This class of models allows ̄exible functional dependence of an outcome variable on covariates by using nonparametric regression, while accounting for correlation between observations by using random effects. We estimate no...

This article proposes a flexible tracker which can estimate motions and deformations of 3D objects in images by considering their appearances as nonrigid surfaces. In this approach, a flexible model is built by matching local features (key-points) over training sequences and by learning the deformations of a spline based model. A statistical model captures the variations of object appearance ca...

In many statistical applications, nonparametric modeling can provide insights into the features of a dataset that are not obtainable by other means. One successful approach involves the use of (univariate or multivariate) spline spaces. As a class, these methods have inherited much from classical tools for parametric modeling. For example, stepwise variable selection with spline basis terms is ...

conclusions the use of smoothing methods helps us to eliminate non-linear effects but it is more appropriate to use cox proportional hazards model in medical data because of its’ ease of interpretation and capability of modeling both continuous and discrete covariates. also, cox proportional hazards model and smoothing methods analysis identified that age at diagnosis and tumor size were indepe...

in this paper, we solve a linear system of second-order boundary value problems by using the quadratic b-spline nite el- ement method (fem). the performance of the method is tested on one model problem. comparisons are made with both the analyti- cal solution and some recent results.the obtained numerical results show that the method is ecient.

We study a smoothing spline Poisson regression model for the analysis of mortality data. Being a non-parametric approach it is intrinsically robust, that it is a penalized likelihood estimation method makes available an approximate Bayesian confidence interval and importantly the software gss, its implementation on the freely available statistical package R, makes it easily accessible to the us...

1. The problem Let L > 0, η > 0, let A0 : [0, L] → R be a positive function of class C2 such that (A0)′(0) = 0 = (A0)′(L), (1) and let A1 : [0, L] → R be a positive continuous function. Consider the Neumann problem η[A − A0(x)]′′ − A + A0(x) + NA = 0, A(0) = 0 = A(L), (2)  N ′ − 2N A A ′ − NA + A1(x) − A0(x) = 0, N (0) = 0 = N (L). (3) A solution of (2)–(3) is a couple of real functions (A,N)...