Paper Abstract and Keywords |
Presentation |
2019-03-01 09:45
Data Augmentation based on RGB-D SLAM 3D Data Ken Miyamoto, Osamu Tsukahara (MELCO) PRMU2018-124 CNR2018-47 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Large data preparation is inevitable for training a deep neural network. Preparing the large data with handcrafted label is not practical for recognizing an arbitrary object. Hence, various data augmentation methods have been published in the recent years. One of the representatives uses a computer graphics model. It can create images rendered from viewpoints under various light conditions. The second one augments images by translation, rotation or scaling. It is indispensable to train images taken from various viewpoints for recognizing an object on a natural image taken from an arbitrary viewpoint. However, the conventional data augmentations can’t create the images. We propose data augmentation based on 3D data taken through RGB-D SLAM. Our augmentation can create the images with low human cost. A user directs a recognition target area from an image obtained through RGB-D SLAM. The directed area is transformed to 3D positions using pose and depth. Additionally, the 3D positions are projected to all other images for obtaining corresponding directed areas. When training images obtained by the direction, the result shows that the mIoU is better than training images augmented by mix of translation, rotation and flipping. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Data Augmentation / Simultaneous Localization And Mapping / SLAM / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 459, PRMU2018-124, pp. 53-57, Feb. 2019. |
Paper # |
PRMU2018-124 |
Date of Issue |
2019-02-21 (PRMU, CNR) |
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) |
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PRMU2018-124 CNR2018-47 |
Conference Information |
Committee |
PRMU CNR |
Conference Date |
2019-02-28 - 2019-03-01 |
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(See Japanese page) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2019-02-PRMU-CNR |
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Japanese |
Title (in Japanese) |
(See Japanese page) |
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(See Japanese page) |
Title (in English) |
Data Augmentation based on RGB-D SLAM 3D Data |
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Data Augmentation |
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Simultaneous Localization And Mapping |
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SLAM |
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1st Author's Name |
Ken Miyamoto |
1st Author's Affiliation |
Mitsubishi Electric Corporation (MELCO) |
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Osamu Tsukahara |
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Mitsubishi Electric Corporation (MELCO) |
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Speaker |
Author-1 |
Date Time |
2019-03-01 09:45:00 |
Presentation Time |
15 minutes |
Registration for |
PRMU |
Paper # |
PRMU2018-124, CNR2018-47 |
Volume (vol) |
vol.118 |
Number (no) |
no.459(PRMU), no.460(CNR) |
Page |
pp.53-57 |
#Pages |
5 |
Date of Issue |
2019-02-21 (PRMU, CNR) |
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