Best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation

Object manipulation is one of the essential tasks for a home helper robot, especially in helping a disabled person to complete everyday tasks. For handling various objects in a category, accurate pose estimation of the target objects is required. Since the pose of an object is often ambiguous from a...

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Main Authors: Hashim, Nik Mohd Zarifie, Kawanishi, Yasutomo, Deguchi, Daisuke, Ide, Ichiro, Murase, Hiroshi, Amma, Ayako, Kobori, Norimasa
Format: Article
Language:English
Published: Japan Society for Precision Engineering 2021
Online Access:http://eprints.utem.edu.my/id/eprint/25968/2/87_440.PDF
http://eprints.utem.edu.my/id/eprint/25968/
https://www.jstage.jst.go.jp/article/jjspe/87/5/87_440/_pdf/-char/en
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Institution: Universiti Teknikal Malaysia Melaka
Language: English
id my.utem.eprints.25968
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spelling my.utem.eprints.259682023-06-06T16:35:24Z http://eprints.utem.edu.my/id/eprint/25968/ Best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation Hashim, Nik Mohd Zarifie Kawanishi, Yasutomo Deguchi, Daisuke Ide, Ichiro Murase, Hiroshi Amma, Ayako Kobori, Norimasa Object manipulation is one of the essential tasks for a home helper robot, especially in helping a disabled person to complete everyday tasks. For handling various objects in a category, accurate pose estimation of the target objects is required. Since the pose of an object is often ambiguous from an observation, it is important to select a good next-viewpoint to make a better pose estimation. This paper introduces a metric of the object pose ambiguity based on the entropy of the pose estimation result. By using the metric, a best next-viewpoint recommendation method is proposed for accurate category-level object pose estimation. Evaluation is performed with synthetic object images of objects in five categories. It shows the proposed methods is applicable to various kind of object categories. Japan Society for Precision Engineering 2021 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/25968/2/87_440.PDF Hashim, Nik Mohd Zarifie and Kawanishi, Yasutomo and Deguchi, Daisuke and Ide, Ichiro and Murase, Hiroshi and Amma, Ayako and Kobori, Norimasa (2021) Best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation. Journal of the Japan Society for Precision Engineering, 87 (5). pp. 440-446. ISSN 0912-0289 https://www.jstage.jst.go.jp/article/jjspe/87/5/87_440/_pdf/-char/en 10.2493/JJSPE.87.440
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description Object manipulation is one of the essential tasks for a home helper robot, especially in helping a disabled person to complete everyday tasks. For handling various objects in a category, accurate pose estimation of the target objects is required. Since the pose of an object is often ambiguous from an observation, it is important to select a good next-viewpoint to make a better pose estimation. This paper introduces a metric of the object pose ambiguity based on the entropy of the pose estimation result. By using the metric, a best next-viewpoint recommendation method is proposed for accurate category-level object pose estimation. Evaluation is performed with synthetic object images of objects in five categories. It shows the proposed methods is applicable to various kind of object categories.
format Article
author Hashim, Nik Mohd Zarifie
Kawanishi, Yasutomo
Deguchi, Daisuke
Ide, Ichiro
Murase, Hiroshi
Amma, Ayako
Kobori, Norimasa
spellingShingle Hashim, Nik Mohd Zarifie
Kawanishi, Yasutomo
Deguchi, Daisuke
Ide, Ichiro
Murase, Hiroshi
Amma, Ayako
Kobori, Norimasa
Best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation
author_facet Hashim, Nik Mohd Zarifie
Kawanishi, Yasutomo
Deguchi, Daisuke
Ide, Ichiro
Murase, Hiroshi
Amma, Ayako
Kobori, Norimasa
author_sort Hashim, Nik Mohd Zarifie
title Best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation
title_short Best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation
title_full Best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation
title_fullStr Best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation
title_full_unstemmed Best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation
title_sort best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation
publisher Japan Society for Precision Engineering
publishDate 2021
url http://eprints.utem.edu.my/id/eprint/25968/2/87_440.PDF
http://eprints.utem.edu.my/id/eprint/25968/
https://www.jstage.jst.go.jp/article/jjspe/87/5/87_440/_pdf/-char/en
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