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Paper Abstract and Keywords
Presentation 2017-03-07 13:00
Deep Learning Approach for Moving Object Tracking using Microwave Doppler Signals
Motoko Tachibana, Michiyo Hiramoto, Kurato Maeno (OKI) ITS2016-82
Abstract (in Japanese) (See Japanese page) 
(in English) In this report, we present a study on tracking using Microwave Doppler Sensor adopting deep learning approach.
Measurement of moving object by Microwave Doppler Sensor is more stable than by camera, because it is little susceptible for environment factor, such as weather or lighting. For the purpose, firstly we have to track moving objects which are detected at every sampling time. However, under the condition which two or more objects move at similar speed and are at near positions it is difficult to distinguish them. Therefore, we have adopted deep learning approach for tracking objects in order to solve these difficulties. Concretely, we have created deep convolutional network model for comparison procedure which evaluate whether one of the observed value corresponds with one of the observed value history coordinated by objects. As a result, we achieved high accuracy for the comparison.
Keyword (in Japanese) (See Japanese page) 
(in English) Microwave Doppler Sensor / Tracking / Deep Learning / / / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 502, ITS2016-82, pp. 31-35, March 2017.
Paper # ITS2016-82 
Date of Issue 2017-02-28 (ITS) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 ITS2016-82

Conference Information
Committee ITS IEE-ITS  
Conference Date 2017-03-07 - 2017-03-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyoto Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Information Processing for ITS, etc. 
Paper Information
Registration To ITS 
Conference Code 2017-03-ITS-ITS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Deep Learning Approach for Moving Object Tracking using Microwave Doppler Signals 
Sub Title (in English)  
Keyword(1) Microwave Doppler Sensor  
Keyword(2) Tracking  
Keyword(3) Deep Learning  
1st Author's Name Motoko Tachibana  
1st Author's Affiliation Oki Electric Industry Co., Ltd. (OKI)
2nd Author's Name Michiyo Hiramoto  
2nd Author's Affiliation Oki Electric Industry Co., Ltd. (OKI)
3rd Author's Name Kurato Maeno  
3rd Author's Affiliation Oki Electric Industry Co., Ltd. (OKI)
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Speaker Author-1 
Date Time 2017-03-07 13:00:00 
Presentation Time 20 minutes 
Registration for ITS 
Paper # ITS2016-82 
Volume (vol) vol.116 
Number (no) no.502 
Page pp.31-35 
Date of Issue 2017-02-28 (ITS) 

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