| Paper Abstract and Keywords |
| Presentation |
2017-03-14 14:35
Discrimination of drowsiness level based on facial skin thermogram using CNN Hiroko Adachi, Kosuke Oiwa, Akio Nozawa (AGU) MBE2016-99 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
The relation between drowsiness and facial expression can be classified into five levels according to NEDO method which is the method of objective evaluation for drowsiness. On the other hand, facial skin temperature changes with drowsiness according to physiological mechanism. In this study, we attempted to construct a discrimination modeling for drowsiness using facial skin temperature and facial expression by Convolutional Neural Network. As a result, the maximum of discrimination rate of the model using facial skin temperature was 90.3% and was 14.9% higher than that of the model using facial expression. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Induced Drowsiness / Thermal Image / Facial Skin Temperature / Deep Learning / Convolutional Neural Network / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 116, no. 520, MBE2016-99, pp. 83-86, March 2017. |
| Paper # |
MBE2016-99 |
| Date of Issue |
2017-03-06 (MBE) |
| 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. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
| Download PDF |
MBE2016-99 |
| Conference Information |
| Committee |
MBE NC |
| Conference Date |
2017-03-13 - 2017-03-14 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Kikai-Shinko-Kaikan Bldg. |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
|
| Paper Information |
| Registration To |
MBE |
| Conference Code |
2017-03-MBE-NC |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Discrimination of drowsiness level based on facial skin thermogram using CNN |
| Sub Title (in English) |
|
| Keyword(1) |
Induced Drowsiness |
| Keyword(2) |
Thermal Image |
| Keyword(3) |
Facial Skin Temperature |
| Keyword(4) |
Deep Learning |
| Keyword(5) |
Convolutional Neural Network |
| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Hiroko Adachi |
| 1st Author's Affiliation |
Aoyama Gakuin University (AGU) |
| 2nd Author's Name |
Kosuke Oiwa |
| 2nd Author's Affiliation |
Aoyama Gakuin University (AGU) |
| 3rd Author's Name |
Akio Nozawa |
| 3rd Author's Affiliation |
Aoyama Gakuin University (AGU) |
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| Speaker |
Author-1 |
| Date Time |
2017-03-14 14:35:00 |
| Presentation Time |
25 minutes |
| Registration for |
MBE |
| Paper # |
MBE2016-99 |
| Volume (vol) |
vol.116 |
| Number (no) |
no.520 |
| Page |
pp.83-86 |
| #Pages |
4 |
| Date of Issue |
2017-03-06 (MBE) |