Paper Abstract and Keywords |
Presentation |
2019-12-20 15:55
Occlusion-Robust Pose-Feature Representation Learning for Object Pose Estimation from a Depth Image Hiroki Tatemichi, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.), Ayako Amma (Toyota) PRMU2019-62 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In order for a robot to carry an object, it is necessary to estimate the pose of the object. However, when an object is occluded by other objects, the observation is partially lost and the object center is shifted in the cropped depth image. Therefore, the pose estimation of an occluded object is difficult. In the proposed method, we realize the pose estimation from the pose representation obtained by de-occluding and centerizing the object in the image via AutoEncoder that have been trained so as to de-occlude it. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Depth Image / Occlusion / Object Pose Estimation / AutoEncoder / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 347, PRMU2019-62, pp. 99-104, Dec. 2019. |
Paper # |
PRMU2019-62 |
Date of Issue |
2019-12-12 (PRMU) |
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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PRMU2019-62 |
Conference Information |
Committee |
PRMU |
Conference Date |
2019-12-19 - 2019-12-20 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
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Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2019-12-PRMU |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Occlusion-Robust Pose-Feature Representation Learning for Object Pose Estimation from a Depth Image |
Sub Title (in English) |
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Keyword(1) |
Depth Image |
Keyword(2) |
Occlusion |
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Object Pose Estimation |
Keyword(4) |
AutoEncoder |
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1st Author's Name |
Hiroki Tatemichi |
1st Author's Affiliation |
Nagoya University (Nagoya Univ.) |
2nd Author's Name |
Yasutomo Kawanishi |
2nd Author's Affiliation |
Nagoya University (Nagoya Univ.) |
3rd Author's Name |
Daisuke Deguchi |
3rd Author's Affiliation |
Nagoya University (Nagoya Univ.) |
4th Author's Name |
Ichiro Ide |
4th Author's Affiliation |
Nagoya University (Nagoya Univ.) |
5th Author's Name |
Hiroshi Murase |
5th Author's Affiliation |
Nagoya University (Nagoya Univ.) |
6th Author's Name |
Ayako Amma |
6th Author's Affiliation |
Toyota Motor Corporation (Toyota) |
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Speaker |
Author-1 |
Date Time |
2019-12-20 15:55:00 |
Presentation Time |
15 minutes |
Registration for |
PRMU |
Paper # |
PRMU2019-62 |
Volume (vol) |
vol.119 |
Number (no) |
no.347 |
Page |
pp.99-104 |
#Pages |
6 |
Date of Issue |
2019-12-12 (PRMU) |
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