We explore three papers concerned with two methods for incorporating discrete, noisy, incomplete dissimilarity data into statistical/machine learning models for supervised, semisupervised or unsupervised machine learning. The two methods are RKE (Regularized Kernel Estimation), and RMU (Regularized Manifold Unfolding). Briefly put, the methods use dissimilarity information between objects in a ...

PURPOSE The aim of this study was to compare the coordinates of anatomical landmarks on cone-beam computed tomographic (CBCT) images in varied head positions before and after reorientation using image analysis software. MATERIALS AND METHODS CBCT images were taken in a normal position and four varied head positions using a dry skull marked with 3 points where gutta percha was fixed. In each o...

Often multidimensional data are visualized by splitting n-D data to a set of low dimensional data. While it is useful it destroys integrity of n-D data, and leads to a shallow understanding complex n-D data. To mitigate this challenge a difficult perceptual task of assembling low-dimensional visualized pieces to the whole n-D vectors must be solved. Another way is a lossy dimension reduction by...

At present, with the popularity of multimedia, people's appreciation and interest in ink painting art have been deepened. In research works, this paper proposes a rendering method three-dimensional effect based on deep learning model, which can simulate skills terms intensity distance. Specifically, first construct two-dimensional texture, then map horizontal component texture using contour inf...

Barycentric coordinates are a fundamental concept in computer graphics and geometric modeling. We extend the geometric construction of Floater’s mean value coordinates [8,11] to a general form that is capable of constructing a family of coordinates in a convex 2D polygon, 3D triangular polyhedron, or a higher-dimensional simplicial polytope. This family unifies previously known coordinates, inc...

Typically machine vision systems estimate ranges using stereoscopic vision systems or specialized range detectors. Although these methods are effective, they are expensive. In this paper, a single camera range estimation algorithm is developed for a low-cost machine vision system that uses off-the-shelf components. This algorithm uses the perspective transformation and a priori knowledge of sce...

We show that the infinite-dimensional Teichmüller space of a Riemann surface whose boundary consists of n closed curves is a holomorphic fiber space over the Teichmüller space of n-punctured surfaces. Each fiber is a complex Banach manifold modeled on a twodimensional extension of the universal Teichmüller space. The local model of the fiber, together with the coordinates from internal Schiffer...

Visualizing multi-dimensional data has tremendous effects on science, engineering, and business decisionmaking. A new visualization technique called Star Coordinates is presented to support users in early stages of their visual thinking activities. Star Coordinates arranges coordinates on a circle sharing the same origin at the center. It uses simply points to represent data, treating each dime...

Barycentric coordinates are well known and used in many applications. They are used for a position computation inside of an (n+1)-sided simplex in an n-dimensional space, i.e. in a triangle in E or in a tetrahedron in E. There are some cases when the given point is theoretically on the hyperplane, i.e. on a plane in E, but due to numerical imprecision is actually not. Also in some cases we need...

Parametric cubic spline curves are commonly used to model the geometry of road surfaces in real-time driving simulators. Roads are represented by space curves that define a curvilinear frame of reference in which three-dimensional points are expressed in coordinates of distance along the curve, offset from the central axis, and loft from the road surface. Simulators must map from global Cartesi...