Detail publikačního výsledku

Fast total least squares vectorization

JELÍNEK, A.; ŽALUD, L.; JÍLEK, T.

Originální název

Fast total least squares vectorization

Anglický název

Fast total least squares vectorization

Druh

Článek WoS

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.

Anglický 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

Klíčová slova v angličtině

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

Autoři

JELÍNEK, A.; ŽALUD, L.; JÍLEK, T.

Rok RIV

2018

Vydáno

01.04.2019

Nakladatel

Springer Berlin Heidelberg

ISSN

1861-8219

Periodikum

Journal of Real-Time Image Processing

Svazek

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="1861-8200",
  url="https://link.springer.com/article/10.1007/s11554-016-0562-6"
}