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| Presentation | 2018-09-21 10:10 [Short Paper] Kinect RGB-D Hand Gesture Image Database for Deep Learning-Based Gesture Recognition Jiaqing Liu, Kotaro Furusawa, Seiju Tsujinaga (Ritsu), Tomoko Tateyama (Hiroshima), Yutaro Iwamoto, YenWei Chen (Ritsu)  PRMU2018-58 IBISML2018-35 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | We present a new dataset named the MaHG-RGBD, a multi-angle view hand gesture for deep learning-based gesture recognition. This dataset has the following features compared with the existing ones. Firstly, both depth and color of segmented hand region images are recorded at the same time. Secondly, by using two camera views to capture hand gestures: our dataset allows researchers to combine information from multiple angles to overcome the ambiguity in gestures recognition. Thirdly, the various of different gestures classes: a total of 25 classes. Finally, we evaluate the recognition accuracy of 25 different hand gestures using deep learning methods to form a benchmark on this dataset. The MaHG-RGBD dataset is available at the link: http://www.iipl.is.ritsumei.ac.jp/MaHG-RGBD. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | R-GBD Dataset / hand gestures / multi-angle view / deep learning / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 219, PRMU2018-58, pp. 141-142, Sept. 2018. | |
| Paper # | PRMU2018-58 | |
| Date of Issue | 2018-09-13 (PRMU, IBISML) | |
| 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 | PRMU2018-58 IBISML2018-35 |
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| Conference Information | |
| Committee | PRMU IBISML IPSJ-CVIM |
| Conference Date | 2018-09-20 - 2018-09-21 |
| 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 | 2018-09-PRMU-IBISML-CVIM |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Kinect RGB-D Hand Gesture Image Database for Deep Learning-Based Gesture Recognition |
| Sub Title (in English) | |
| Keyword(1) | R-GBD Dataset |
| Keyword(2) | hand gestures |
| Keyword(3) | multi-angle view |
| Keyword(4) | deep learning |
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| 1st Author's Name | Jiaqing Liu |
| 1st Author's Affiliation | Ritsumeikan University (Ritsu) |
| 2nd Author's Name | Kotaro Furusawa |
| 2nd Author's Affiliation | Ritsumeikan University (Ritsu) |
| 3rd Author's Name | Seiju Tsujinaga |
| 3rd Author's Affiliation | Ritsumeikan University (Ritsu) |
| 4th Author's Name | Tomoko Tateyama |
| 4th Author's Affiliation | Hiroshima Institute of Tech (Hiroshima) |
| 5th Author's Name | Yutaro Iwamoto |
| 5th Author's Affiliation | Ritsumeikan University (Ritsu) |
| 6th Author's Name | YenWei Chen |
| 6th Author's Affiliation | Ritsumeikan University (Ritsu) |
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| Speaker | Author-1 |
| Date Time | 2018-09-21 10:10:00 |
| Presentation Time | 10 minutes |
| Registration for | PRMU |
| Paper # | PRMU2018-58, IBISML2018-35 |
| Volume (vol) | vol.118 |
| Number (no) | no.219(PRMU), no.220(IBISML) |
| Page | pp.141-142 |
| #Pages | 2 |
| Date of Issue | 2018-09-13 (PRMU, IBISML) |
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