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| Presentation | 2017-10-12 10:00 Online Human Action Detection using Deep Spatio-temporal Transformation Yukihide Takagaki, Masaki Aono (TUT)  PRMU2017-68 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this research, we describe online human action detection using Convolutional Neural Network which inputs skeleton data of multiple frames. We propose a network that transforms skeleton data into a certain image by the Fully connected layer and uses the image as input to the 3D convolution layer. Furthermore, we output the probability of the action class of the frame, and apply an average filter multiple times to the probability among frames for improvement of performance. In the experiment, we compared online human action detection accuracy between conventional method and proposed method using Online Action Detection Dataset consisting of skeleton data, image data, and depth data of human action. As a result, we could improve the performance of our method against conventional methods. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Skeleton / Online Action Detection / Transform / CNN / Temporal Localization / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 238, PRMU2017-68, pp. 31-35, Oct. 2017. | |
| Paper # | PRMU2017-68 | |
| Date of Issue | 2017-10-05 (PRMU) | |
| 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 | PRMU2017-68 |
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| Conference Information | |
| Committee | PRMU |
| Conference Date | 2017-10-12 - 2017-10-13 |
| 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 | 2017-10-PRMU |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Online Human Action Detection using Deep Spatio-temporal Transformation |
| Sub Title (in English) | |
| Keyword(1) | Skeleton |
| Keyword(2) | Online Action Detection |
| Keyword(3) | Transform |
| Keyword(4) | CNN |
| Keyword(5) | Temporal Localization |
| Keyword(6) | |
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| Keyword(8) | |
| 1st Author's Name | Yukihide Takagaki |
| 1st Author's Affiliation | Toyohashi University of Technology (TUT) |
| 2nd Author's Name | Masaki Aono |
| 2nd Author's Affiliation | Toyohashi University of Technology (TUT) |
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| Speaker | Author-1 |
| Date Time | 2017-10-12 10:00:00 |
| Presentation Time | 30 minutes |
| Registration for | PRMU |
| Paper # | PRMU2017-68 |
| Volume (vol) | vol.117 |
| Number (no) | no.238 |
| Page | pp.31-35 |
| #Pages | 5 |
| Date of Issue | 2017-10-05 (PRMU) |
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