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Paper Abstract and Keywords
Presentation 2018-02-20 09:30
Detection of outdoor cables from point-cloud measured by MMS -- Classification method of elongated object using histogram feature based on multiple geometric directions(MGPFH) --
Hitoshi Niigaki, Ken Tsutsuguchi, Tetsuya Kinebuchi (NTT) PRMU2017-159 CNR2017-37
Abstract (in Japanese) (See Japanese page) 
(in English) Research results on detecting details of outdoor structures using point clouds measured by Mobile Map-
ping Systems have been reported in recent years. The reports show that unvarying statistics about position and
orientation, obtained by using normal information, have been used as effective feature quantities for identifying 3D
objects. However, since many such structures have elongated (“swept”) shapes, it is often difficult to extract the
normal information stably. In urban areas, the scale for extracting features often increases due to the effects of
neighboring structures. In such cases, features extracted from point clouds of other structures get mixed together.
This makes it difficult to obtain features effective for identification. We found in our work that the amount of statis-
tics in the extrusion direction effectively enables swept shapes to be identified with high accuracy, even when there
are multiple adjacent objects. We also found that the identification accuracy improves by using feature quantities
extracted explicitly from the region of interest and the surrounding regions.
Keyword (in Japanese) (See Japanese page) 
(in English) point-cloud / MMS / 3D feature / 3D object / cross section / clustering / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 442, PRMU2017-159, pp. 83-87, Feb. 2018.
Paper # PRMU2017-159 
Date of Issue 2018-02-12 (PRMU, CNR) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF PRMU2017-159 CNR2017-37

Conference Information
Committee PRMU CNR  
Conference Date 2018-02-19 - 2018-02-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2018-02-PRMU-CNR 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Detection of outdoor cables from point-cloud measured by MMS 
Sub Title (in English) Classification method of elongated object using histogram feature based on multiple geometric directions(MGPFH) 
Keyword(1) point-cloud  
Keyword(2) MMS  
Keyword(3) 3D feature  
Keyword(4) 3D object  
Keyword(5) cross section  
Keyword(6) clustering  
Keyword(7)  
Keyword(8)  
1st Author's Name Hitoshi Niigaki  
1st Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
2nd Author's Name Ken Tsutsuguchi  
2nd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
3rd Author's Name Tetsuya Kinebuchi  
3rd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
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Speaker Author-1 
Date Time 2018-02-20 09:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2017-159, CNR2017-37 
Volume (vol) vol.117 
Number (no) no.442(PRMU), no.443(CNR) 
Page pp.83-87 
#Pages
Date of Issue 2018-02-12 (PRMU, CNR) 


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