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Robust Object Segmentation Using a Multi-Layer Laser Scanner

The major problem in an advanced driver assistance system (ADAS) is the proper use of sensor measurements and recognition of the surrounding environment. To this end, there are several types of sensors to consider, one of which is the laser scanner. In this paper, we propose a method to segment the...

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Autores principales: Kim, Beomseong, Choi, Baehoon, Yoo, Minkyun, Kim, Hyunju, Kim, Euntai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4279490/
https://www.ncbi.nlm.nih.gov/pubmed/25356645
http://dx.doi.org/10.3390/s141120400
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author Kim, Beomseong
Choi, Baehoon
Yoo, Minkyun
Kim, Hyunju
Kim, Euntai
author_facet Kim, Beomseong
Choi, Baehoon
Yoo, Minkyun
Kim, Hyunju
Kim, Euntai
author_sort Kim, Beomseong
collection PubMed
description The major problem in an advanced driver assistance system (ADAS) is the proper use of sensor measurements and recognition of the surrounding environment. To this end, there are several types of sensors to consider, one of which is the laser scanner. In this paper, we propose a method to segment the measurement of the surrounding environment as obtained by a multi-layer laser scanner. In the segmentation, a full set of measurements is decomposed into several segments, each representing a single object. Sometimes a ghost is detected due to the ground or fog, and the ghost has to be eliminated to ensure the stability of the system. The proposed method is implemented on a real vehicle, and its performance is tested in a real-world environment. The experiments show that the proposed method demonstrates good performance in many real-life situations.
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spelling pubmed-42794902015-01-15 Robust Object Segmentation Using a Multi-Layer Laser Scanner Kim, Beomseong Choi, Baehoon Yoo, Minkyun Kim, Hyunju Kim, Euntai Sensors (Basel) Article The major problem in an advanced driver assistance system (ADAS) is the proper use of sensor measurements and recognition of the surrounding environment. To this end, there are several types of sensors to consider, one of which is the laser scanner. In this paper, we propose a method to segment the measurement of the surrounding environment as obtained by a multi-layer laser scanner. In the segmentation, a full set of measurements is decomposed into several segments, each representing a single object. Sometimes a ghost is detected due to the ground or fog, and the ghost has to be eliminated to ensure the stability of the system. The proposed method is implemented on a real vehicle, and its performance is tested in a real-world environment. The experiments show that the proposed method demonstrates good performance in many real-life situations. MDPI 2014-10-29 /pmc/articles/PMC4279490/ /pubmed/25356645 http://dx.doi.org/10.3390/s141120400 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Beomseong
Choi, Baehoon
Yoo, Minkyun
Kim, Hyunju
Kim, Euntai
Robust Object Segmentation Using a Multi-Layer Laser Scanner
title Robust Object Segmentation Using a Multi-Layer Laser Scanner
title_full Robust Object Segmentation Using a Multi-Layer Laser Scanner
title_fullStr Robust Object Segmentation Using a Multi-Layer Laser Scanner
title_full_unstemmed Robust Object Segmentation Using a Multi-Layer Laser Scanner
title_short Robust Object Segmentation Using a Multi-Layer Laser Scanner
title_sort robust object segmentation using a multi-layer laser scanner
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4279490/
https://www.ncbi.nlm.nih.gov/pubmed/25356645
http://dx.doi.org/10.3390/s141120400
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