論文

査読有り
2016年

Intensity Histogram Based Segmentation of 3D Point Cloud Using Growing Neural Gas

INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2016, PT II
  • Shin Miyake
  • ,
  • Yuichiro Toda
  • ,
  • Naoyuki Kubota
  • ,
  • Naoyuki Takesue
  • ,
  • Kazuyoshi Wada

9835
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
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
  • 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

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