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Paper Abstract and Keywords
Presentation 2017-05-28 10:45
A study on JSL Finger Spelling Recognition Using Convolutional Neural Networks
Shinji Sako, Hana Hosoe (NIT), Bogdan Kwolek (AGH) WIT2017-10
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, a few methods for recognition of hand postures on depth maps using convolutional neural networks were proposed. In this paper, we present a framework for recognition of static finger spelling in Japanese Sign Language. The recognition takes place on the basis of single gray image. The finger spelled signs are recognized using a convolutional neural network. A dataset consisting of 5000 samples has been recorded. A 3D articulated hand model has been designed to generate synthetic finger spellings and to extend the real hand gestures. Experimental results demonstrate that owing to sufficient amount of training data a high recognition rate can be attained on images from a single RGB camera. The full dataset and Caffe model are available for download.
Keyword (in Japanese) (See Japanese page) 
(in English) sign language, / finger spelling recognition / convolutional neural networks / / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 66, WIT2017-10, pp. 45-49, May 2017.
Paper # WIT2017-10 
Date of Issue 2017-05-20 (WIT) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
and
reproduction
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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF WIT2017-10

Conference Information
Committee WIT ASJ-H  
Conference Date 2017-05-27 - 2017-05-28 
Place (in Japanese) (See Japanese page) 
Place (in English) RION Co., LTD. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Psychological and Physiological Acoustics and Well-being Information Technology, etc. 
Paper Information
Registration To WIT 
Conference Code 2017-05-WIT-H 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A study on JSL Finger Spelling Recognition Using Convolutional Neural Networks 
Sub Title (in English)  
Keyword(1) sign language,  
Keyword(2) finger spelling recognition  
Keyword(3) convolutional neural networks  
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1st Author's Name Shinji Sako  
1st Author's Affiliation Nagoya Institute of Technology (NIT)
2nd Author's Name Hana Hosoe  
2nd Author's Affiliation Nagoya Institute of Technology (NIT)
3rd Author's Name Bogdan Kwolek  
3rd Author's Affiliation AGH University of Technology (AGH)
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Speaker
Date Time 2017-05-28 10:45:00 
Presentation Time 25 
Registration for WIT 
Paper # IEICE-WIT2017-10 
Volume (vol) IEICE-117 
Number (no) no.66 
Page pp.45-49 
#Pages IEICE-5 
Date of Issue IEICE-WIT-2017-05-20 


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