Publication detail

Fast total least squares vectorization

JELÍNEK, A. ŽALUD, L. JÍLEK, T.

Original Title

Fast total least squares vectorization

Type

journal article in Web of Science

Language

English

Original Abstract

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.

Keywords

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

Authors

JELÍNEK, A.; ŽALUD, L.; JÍLEK, T.

Released

1. 4. 2019

Publisher

Springer Berlin Heidelberg

ISBN

1861-8219

Periodical

Journal of Real-Time Image Processing

Year of study

11

Number

1

State

Federal Republic of Germany

Pages from

459

Pages to

475

Pages count

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"
}