Sentence examples for large point sets from inspiring English sources

We propose an algorithm for computing the exact minimum enclosing ball of large point sets in general dimensions.

We have implemented the hybrid algorithm on commodity GPUs, and evaluated its performance on several large point sets.

Given two large point sets P and Q, matching approximatively congruent sets of points over the entire data set is not feasible.

Consequently, the matrix corresponding to the actual placement of the object in the second system must be pre-multiplied by the transformation matrix M. Iteration over large points sets as well as performing matrix operations is very time-consuming.

This paper presents a flexible method to reconstruct simplified mesh surfaces from large unstructured point sets, extending recent work on dynamic surface reconstruction.

In this paper, an algorithm is proposed to determine the extreme points in a large 3D point set along multiple directions.

The main problem we consider is the largest common point set (LCP) problem under the RMSD, a well-known problem in protein structure alignment.

Protein structure alignment is often modeled as the largest common point set (LCP) problem based on the Root Mean Square Deviation (RMSD), a measure commonly used to evaluate structural similarity.

A large value of disconnectivity indicates a better separation of the point sets.

To overcome this challenge, we perform a large number of independent point set matches and generate an ensemble of candidate solutions.

How this happened will set up a larger point, after we examine the other weapons.