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| Paper Abstract and Keywords | ||
| Presentation | 2022-12-23 14:00 Estimate students' concentration level by using facial expression Guan-yun Wang, Hikaru Nagata, Yasuhiro Hatori, Yoshiyuki Sato, Chia-huei Tseng, Satoshi Shioiri (Tohoku Univ.)  HIP2022-70 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Concentration and learning performance of all the students are difficult to track throughout courses. The study recruited 13 participants and asked them to solve a problem used in the International Olympiad of Linguistics in 2018 using a website designed for the task. Participants’ face videos were recorded while they were solving the problems. Action Unit codes (AU), which are facial features related to expressions were extracted with an open-source software, Openface. One of authors evaluated the recorded face to classify the participants into “strongly engaged” group and “weakly engaged” group for the first attepmt. We used lightGBM to train a model to classify the participants into the two groups using AUs extracted by Openface. The classification accuracy of testing data evaluated by five validation method was 95.1%. The intensity of AU04, AU17 and AU25 are the best three features to contribute to the classification. They are “brow lowerer”, “chin raiser” and “lips part”, which suggest that facial features of eyes, cheek and mouth are important to estimate engagement levels. The present study further analyze the mental states of the participants, the classification accuracy was 73.9% using the same classify method as mentioned. Several feature sets for classifier training were discussed in the present study. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | machine learning / facial expression / concentration / classification / action units codes / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 326, HIP2022-70, pp. 65-69, Dec. 2022. | |
| Paper # | HIP2022-70 | |
| Date of Issue | 2022-12-15 (HIP) | |
| ISSN | 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 | HIP2022-70 |
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| Conference Information | |
| Committee | HIP |
| Conference Date | 2022-12-22 - 2022-12-23 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Research Institute of Electrical Communication |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Multi-modal, KANSEI information processing, Vision and its application, Lifelong sciences, Human information processing |
| Paper Information | |
| Registration To | HIP |
| Conference Code | 2022-12-HIP |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Estimate students' concentration level by using facial expression |
| Sub Title (in English) | |
| Keyword(1) | machine learning |
| Keyword(2) | facial expression |
| Keyword(3) | concentration |
| Keyword(4) | classification |
| Keyword(5) | action units codes |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Guan-yun Wang |
| 1st Author's Affiliation | Tohoku University (Tohoku Univ.) |
| 2nd Author's Name | Hikaru Nagata |
| 2nd Author's Affiliation | Tohoku University (Tohoku Univ.) |
| 3rd Author's Name | Yasuhiro Hatori |
| 3rd Author's Affiliation | Tohoku University (Tohoku Univ.) |
| 4th Author's Name | Yoshiyuki Sato |
| 4th Author's Affiliation | Tohoku University (Tohoku Univ.) |
| 5th Author's Name | Chia-huei Tseng |
| 5th Author's Affiliation | Tohoku University (Tohoku Univ.) |
| 6th Author's Name | Satoshi Shioiri |
| 6th Author's Affiliation | Tohoku University (Tohoku Univ.) |
| Speaker | Author-1 |
| Date Time | 2022-12-23 14:00:00 |
| Presentation Time | 30 minutes |
| Registration for | HIP |
| Paper # | HIP2022-70 |
| Volume (vol) | vol.122 |
| Number (no) | no.326 |
| Page | pp.65-69 |
| #Pages | 5 |
| Date of Issue | 2022-12-15 (HIP) |
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