Detail publikace

Fast total least squares vectorization

JELÍNEK, A. ŽALUD, L. JÍLEK, T.

Originální název

Fast total least squares vectorization

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

This paper proposes a novel algorithm for the vectorization of ordered sets of points, named Fast Total Least Squares (FTLS) vectorization. The emphasis was put on low computational complexity, which allows it to be run online on a mobile device at a speed comparable to the fastest algorithms, such as the Douglas–Peucker (DP) algorithm, while maintaining a much higher quality of the approximation. Our approach is based on the total least squares method, therefore all the points from the cloud contribute to its approximation. This leads to better utilization of the information contained in the point cloud, compared to those algorithms based on point elimination, such as DP. Several experiments and performance comparisons are presented to demonstrate the most important attributes of the FTLS algorithm.

Klíčová slova

Point cloud;Vectorization;Least squares;Robotics;Linear regression

Autoři

JELÍNEK, A.; ŽALUD, L.; JÍLEK, T.

Vydáno

1. 4. 2019

Nakladatel

Springer Berlin Heidelberg

ISSN

1861-8219

Periodikum

Journal of Real-Time Image Processing

Ročník

11

Číslo

1

Stát

Spolková republika Německo

Strany od

459

Strany do

475

Strany počet

17

URL

https://link.springer.com/article/10.1007/s11554-016-0562-6

BibTex

@article{BUT120961,
  author="Aleš {Jelínek} and Luděk {Žalud} and Tomáš {Jílek}",
  title="Fast total least squares vectorization",
  journal="Journal of Real-Time Image Processing",
  year="2019",
  volume="11",
  number="1",
  pages="459--475",
  doi="10.1007/s11554-016-0562-6",
  issn="1861-8219",
  url="https://link.springer.com/article/10.1007/s11554-016-0562-6"
}