Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps

Sven Hellbach; Marian Himstedt; Frank Bahrmann; Martin Riedel; Thomas Villmann; Hans-Joachim Böhme

doi:10.1007/978-3-319-07695-9_13

Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps

Sven Hellbach, Marian Himstedt, Frank Bahrmann, Martin Riedel, Thomas Villmann, Hans-Joachim Böhme

Abstract

This paper aims at an approach for labeling places within a grid cell environment. For that we propose a method that is based on non-negative matrix factorization (NMF) to extract environment specific features from a given occupancy grid map. NMF also computes a description about where on the map these features need to be applied. We use this description after certain pre-processing steps as an input for generalized learning vector quantization (GLVQ) to achieve the classification or labeling of the grid cells. Our approach is evaluated on a standard data set from University of Freiburg, showing very promising results.

Originalsprache	Englisch
Titel	Advances in Self-Organizing Maps and Learning Vector Quantization
Redakteure/-innen	Thomas Villmann, Frank-Michael Schleif, Marika Kaden, Mandy Lange
Seitenumfang	11
Erscheinungsort	Cham
Herausgeber (Verlag)	Springer International Publishing
Erscheinungsdatum	01.07.2014
Seiten	133-143
ISBN (Print)	978-3-319-07694-2
ISBN (elektronisch)	978-3-319-07695-9
DOIs	https://doi.org/10.1007/978-3-319-07695-9_13
Publikationsstatus	Veröffentlicht - 01.07.2014
Extern publiziert	Ja
Veranstaltung	Proceedings of the 10th International Workshop on Advances in Self-Organizing Maps and Learning Vector Quantization - Mittweida, Deutschland Dauer: 02.07.2014 → 04.07.2014

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10.1007/978-3-319-07695-9_13

Weitere Links

https://www.scopus.com/pages/publications/84903516416

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Hellbach, S., Himstedt, M., Bahrmann, F., Riedel, M., Villmann, T., & Böhme, H.-J. (2014). Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps. in T. Villmann, F.-M. Schleif, M. Kaden, & M. Lange (Hrsg.), Advances in Self-Organizing Maps and Learning Vector Quantization (S. 133-143). (Advances in Intelligent Systems and Computing). Springer International Publishing. https://doi.org/10.1007/978-3-319-07695-9_13

Hellbach, Sven ; Himstedt, Marian ; Bahrmann, Frank et al. / Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps. Advances in Self-Organizing Maps and Learning Vector Quantization. Hrsg. / Thomas Villmann ; Frank-Michael Schleif ; Marika Kaden ; Mandy Lange. Cham : Springer International Publishing, 2014. S. 133-143 (Advances in Intelligent Systems and Computing).

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title = "Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps",

abstract = "This paper aims at an approach for labeling places within a grid cell environment. For that we propose a method that is based on non-negative matrix factorization (NMF) to extract environment specific features from a given occupancy grid map. NMF also computes a description about where on the map these features need to be applied. We use this description after certain pre-processing steps as an input for generalized learning vector quantization (GLVQ) to achieve the classification or labeling of the grid cells. Our approach is evaluated on a standard data set from University of Freiburg, showing very promising results.",

author = "Sven Hellbach and Marian Himstedt and Frank Bahrmann and Martin Riedel and Thomas Villmann and Hans-Joachim B{\"o}hme",

year = "2014",

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booktitle = "Advances in Self-Organizing Maps and Learning Vector Quantization",

note = "Proceedings of the 10th International Workshop on Advances in Self-Organizing Maps and Learning Vector Quantization, WSOM 2014 ; Conference date: 02-07-2014 Through 04-07-2014",

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Hellbach, S, Himstedt, M, Bahrmann, F, Riedel, M, Villmann, T & Böhme, H-J 2014, Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps. in T Villmann, F-M Schleif, M Kaden & M Lange (Hrsg.), Advances in Self-Organizing Maps and Learning Vector Quantization. Advances in Intelligent Systems and Computing, Springer International Publishing, Cham, S. 133-143, Proceedings of the 10th International Workshop on Advances in Self-Organizing Maps and Learning Vector Quantization, Mittweida, Sachsen, Deutschland, 02.07.14. https://doi.org/10.1007/978-3-319-07695-9_13

Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps. / Hellbach, Sven; Himstedt, Marian; Bahrmann, Frank et al.
Advances in Self-Organizing Maps and Learning Vector Quantization. Hrsg. / Thomas Villmann; Frank-Michael Schleif; Marika Kaden; Mandy Lange. Cham: Springer International Publishing, 2014. S. 133-143 (Advances in Intelligent Systems and Computing).

Publikation: Kapitel in Büchern/Berichten/Konferenzbänden › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps

AU - Hellbach, Sven

AU - Himstedt, Marian

AU - Bahrmann, Frank

AU - Riedel, Martin

AU - Villmann, Thomas

AU - Böhme, Hans-Joachim

PY - 2014/7/1

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N2 - This paper aims at an approach for labeling places within a grid cell environment. For that we propose a method that is based on non-negative matrix factorization (NMF) to extract environment specific features from a given occupancy grid map. NMF also computes a description about where on the map these features need to be applied. We use this description after certain pre-processing steps as an input for generalized learning vector quantization (GLVQ) to achieve the classification or labeling of the grid cells. Our approach is evaluated on a standard data set from University of Freiburg, showing very promising results.

AB - This paper aims at an approach for labeling places within a grid cell environment. For that we propose a method that is based on non-negative matrix factorization (NMF) to extract environment specific features from a given occupancy grid map. NMF also computes a description about where on the map these features need to be applied. We use this description after certain pre-processing steps as an input for generalized learning vector quantization (GLVQ) to achieve the classification or labeling of the grid cells. Our approach is evaluated on a standard data set from University of Freiburg, showing very promising results.

UR - https://www.scopus.com/pages/publications/84903516416

U2 - 10.1007/978-3-319-07695-9_13

DO - 10.1007/978-3-319-07695-9_13

M3 - Conference contribution

SN - 978-3-319-07694-2

T3 - Advances in Intelligent Systems and Computing

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BT - Advances in Self-Organizing Maps and Learning Vector Quantization

A2 - Villmann, Thomas

A2 - Schleif, Frank-Michael

A2 - Kaden, Marika

A2 - Lange, Mandy

PB - Springer International Publishing

CY - Cham

T2 - Proceedings of the 10th International Workshop on Advances in Self-Organizing Maps and Learning Vector Quantization

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ER -

Hellbach S, Himstedt M, Bahrmann F, Riedel M, Villmann T, Böhme HJ. Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps. in Villmann T, Schleif FM, Kaden M, Lange M, Hrsg., Advances in Self-Organizing Maps and Learning Vector Quantization. Cham: Springer International Publishing. 2014. S. 133-143. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-07695-9_13

Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps

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