DeepAI AI Chat
Log In Sign Up

An Unsupervised, Iterative N-Dimensional Point-Set Registration Algorithm

08/06/2019
by   A. Pasha Hosseinbor, et al.
0

An unsupervised, iterative point-set registration algorithm for an unlabeled (i.e. correspondence between points is unknown) N-dimensional Euclidean point-cloud is proposed. It is based on linear least squares, and considers all possible point pairings and iteratively aligns the two sets until the number of point pairs does not exceed the maximum number of allowable one-to-one pairings.

READ FULL TEXT

page 1

page 2

page 3

page 4

02/07/2017

A New Point-set Registration Algorithm for Fingerprint Matching

A novel minutia-based fingerprint matching algorithm is proposed that em...
08/26/2021

A Robust Loss for Point Cloud Registration

The performance of surface registration relies heavily on the metric use...
01/10/2021

Provably Approximated ICP

The goal of the alignment problem is to align a (given) point cloud P = ...
04/20/2022

Evaluation of Robust Point Set Registration Applied to Automotive Doppler Radar

Point set registration is the process of finding the best alignment betw...
07/10/2019

Barnes-Hut Approximation for Point SetGeodesic Shooting

Geodesic shooting has been successfully applied to diffeo-morphic regist...
07/26/2019

FAKIR : An algorithm for estimating the pose and elementary anatomy of archaeological statues

The digitization of archaeological artefacts has become an essential par...
01/28/2022

DICP: Doppler Iterative Closest Point Algorithm

In this paper, we present a novel algorithm for point cloud registration...