This is a survey of recent developments in smoothing parameter selection for curve estimation. The first goal of this paper is to provide an introduction to the methods available, with discussion at both a practical and also a nontechnical theoretical level, including comparison of methods. The second goal is to provide access to the literature, especially on smoothing parameter selection, but ...

A practical method is proposed for estimating the inertial parameters of robot manipulators with substantial unmodeled joint kiction and actuator dynamics. The manipulator is mounted on a six-axis forcehorque sensor. Sensor measurements and joint velocities recorded during manipulator motion are used to identify the inertial parameters. The unmodeled joint piction and actuator dynamics do not d...

Microaggregation by individual ranking (IR) is an important technique for masking confidential data. While being a successful method for controlling the disclosure risk of observations, IR is also known for its favorable property of having a relatively small effect on the results of statistical analyses. In this paper we conduct a detailed theoretical analysis on the estimation of arbitrary mom...

This Master thesis deals with an approach for 2D-3D pose estimation, which relies on texture information on the surface mesh of an object model. The textured surface mesh is projected in a virtual image, and a block matching algorithm is employed to determine correspondences between midpoints of surface patches to the image data. To facilitate this purpose, the block matching algorithm needs to...

In this paper, we proposed a randomised algorithm to estimate the motion parameters of a planar shape without knowing a priori point-to-point correspondences. By randomly searching points on two shapes measured at different times, we determine the centroids, after which the algorithm proceeds to determine the rotation by searching points on each shape that form congruent polygons. Key-Words: Mo...

Motion parameters estimation is performed by using the local polynomial periodogram. The presented method provides the estimation of velocity and acceleration, simultaneously. It is appropriate for the motion parameters estimation in noisy sequences. Theoretical considerations are illustrated by numerical examples.

Three-dimensional head pose estimation from a single 2D image is a challenging task with extensive applications. Existing approaches lack the capability to deal with multiple pose-related and -unrelated factors in a uniform way. Most of them can provide only one-dimensional yaw estimation and suffer from limited representation ability for out-of-sample testing inputs. These drawbacks lead to li...

This paper describes a method for incorporating the chromin-ance information when estimating motion in a colour image sequence. It is based on a Maximum-Likelihood (ML) formulation of the motion estimation problem which assumes homogeneous additive Gaussian noise in each colour component, with known inter-eld correlation statistics. It deenes a noise-decorrelating colour space transform which p...

In this paper, maximum likelihood estimation have been obtained for two Weibull populations under joint type II censored scheme, which generalize results of Balakrishnan and Rasouli (2008). Moreover, approximate confidence region are also discussed and compared with two Bootstrap confidence regions. A numerical illustration for these new results is given.