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JELÍNEK, A. ŽALUD, L.
Original Title
Augmented Postprocessing of the FTLS Vectorization Algorithm - Approaching to the Globally Optimal Vectorization of the Sorted Point Clouds
Type
conference paper
Language
English
Original Abstract
Vectorization is a widely used technique in many areas, mainly in robotics and image processing. Applications in these domains frequently require both speed (for real-time operation) and accuracy (for maximal information gain). This paper proposes an optimization for the high speed vectorization methods, which leads to nearly optimal results. The FTLS algorithm uses the total least squares method for fitting the lines into the point cloud and the presented augmentation for the refinement of the results, is based on a modified Nelder-Mead method. As shown on several experiments, this approach leads to better utilization of the information contained in the point cloud. As a result, the quality of approximation grows steadily with the number of points being vectorized, which was not achieved before. Performance costs are still comparable to the original algorithm, so the real-time operation is not endangered.
Keywords
Vectorization;Point Cloud;Linear Regression;Least Squares Fitting;Mobile Robotics
Authors
JELÍNEK, A.; ŽALUD, L.
Released
29. 7. 2016
Publisher
SciTePress
Location
Lisabon
ISBN
978-989-758-198-4
Book
Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2016) - Volume 2
Pages from
216
Pages to
223
Pages count
8
URL
https://www.scitepress.org/Link.aspx?doi=10.5220/0005962902160223
Full text in the Digital Library
http://hdl.handle.net/11012/204287
BibTex
@inproceedings{BUT127074, author="Aleš {Jelínek} and Luděk {Žalud}", title="Augmented Postprocessing of the FTLS Vectorization Algorithm - Approaching to the Globally Optimal Vectorization of the Sorted Point Clouds", booktitle="Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2016) - Volume 2", year="2016", pages="216--223", publisher="SciTePress", address="Lisabon", doi="10.5220/0005962902160223", isbn="978-989-758-198-4", url="https://www.scitepress.org/Link.aspx?doi=10.5220/0005962902160223" }