2016年
Intensity Histogram Based Segmentation of 3D Point Cloud Using Growing Neural Gas
INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2016, PT II
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- 巻
- 9835
- 号
- 開始ページ
- 335
- 終了ページ
- 345
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1007/978-3-319-43518-3_33
- 出版者・発行元
- SPRINGER INT PUBLISHING AG
This paper proposes a 3D point cloud segmentation method using a reflection intensity of Laser Range Finder (LRF). In this paper, we use LRF and tilt unit for acquiring a 3D point cloud. First of all, we apply Growing Neural Gas (GNG) to the point cloud for learning a topological structure of the point cloud. Next, we proposed a segmentation method based on an intensity histogram that is composed of the nearest data of each node. Finally, we show experimental results of the proposed method and discuss the effectiveness of the proposed method.
- リンク情報
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- DOI
- https://doi.org/10.1007/978-3-319-43518-3_33
- DBLP
- https://dblp.uni-trier.de/rec/conf/icira/MiyakeTKTW16
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000389020700033&DestApp=WOS_CPL
- URL
- http://dblp.uni-trier.de/db/conf/icira/icira2016-2.html#conf/icira/MiyakeTKTW16
- ID情報
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- DOI : 10.1007/978-3-319-43518-3_33
- ISSN : 0302-9743
- eISSN : 1611-3349
- DBLP ID : conf/icira/MiyakeTKTW16
- Web of Science ID : WOS:000389020700033