Estimating principal curvatures and principal directions of a surface from a polyhedral approximation with a large number of small faces, such as those produced by iso-surface construction algorithms, has become a basic step in many computer vision algorithms. Particularly in those targeted at medical applications. In this paper we describe a method to estimate the tensor of curvature of a surf...

The ventral pelvic skin of the tree frog Hyla japonica expresses two kinds of arginine vasotocin (AVT)-stimulated aquaporins (AQP-h2 and AQP-h3), which affect the capacity of the frog's skin to absorb water. As such, it can be used as a model system for analyzing the molecular mechanisms of water permeability. We investigated AQP dynamics and water permeability in the pelvic skin of H. japonica...

In Radar applications, we are in need to identify the signals from the desired directions and to avoid unwanted signals from the enemies, which can be achieved by using the direction of arrival (DOA) estimation. Now-a-days we also meet the situation to use the power resources in an efficient manner by reducing the power allocation for inessential activities. In this paper, we consider these pro...

This paper reports on a recent study aimed at developing the stress-induced magnetic anisotropy (SMA) technique for characterizing residual stresses in case hardened steel components. The results of SMA measurements performed on flat induction hardened steel discs with different case depths confirm the feasibility of detecting principal stress axes by measuring the angular variation of magnetic...

A new method for speech signal reconstruction is proposed by performing a nonlinear Kernel Principal Component Analysis (KPCA). By the use of kernel functions, one can efficiently compute principal components in high-dimensional feature spaces, and reconstruct vectors mapping from input space by those dominant principal components. As the reconstructed vectors is expressed in high dimensional f...

A new subspace algorithm consistently identifies stochastic state space models directly from given output data, using only semi-infinite block Hankel matrices. Ala~raet-In this paper, we derive a new subspace algorithm to consistently identify stochastic state space models from given output data without forming the covariance matrix and using only semi-infinite block Hankel matrices. The algori...

This paper describes a new surface normal smoothing process which can be used in conjunction with shape-fromshading. Rather than directly smoothing the surface normal vectors, we exert control over their directions by smoothing the field of principal curvature vectors. To do this we develop a topography sensitive smoothing process which overcomes the problems of singularities in the field of pr...

Subtitle A new subspace algorithm consistently identiies stochastic state space models directly from given output data, using only semi-innnite block Hankel matrices. Abstract In this paper, we derive a new subspace algorithm to consistently identify stochastic state space models from given output data without forming the covariance matrix and using only semi-innnite block Hankel matrices. The ...

This paper presents a method for extracting features for illustrating stone tools. Features are detected from unorganized point clouds obtained by a 3D laser scanner. The curvature of each point in the point clouds is estimated by local surface fitting algorithm and used for detecting potential feature points. Feature lines are extracted by directionally growing algorithm. The main idea of our ...