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Authors: Nik Mohd Zarifie Hashim 1 ; Yasutomo Kawanishi 2 ; Daisuke Deguchi 3 ; Ichiro Ide 2 ; Hiroshi Murase 2 ; Ayako Amma 4 and Norimasa Kobori 5

Affiliations: 1 Graduate School of Informatics, Nagoya University, Japan, Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka and Malaysia ; 2 Graduate School of Informatics, Nagoya University and Japan ; 3 Information Strategy Office, Nagoya University and Japan ; 4 Toyota Motor Corporation and Japan ; 5 Toyota Motor Europe and Belgium

Keyword(s): 3D Object, Deep Learning, Next Viewpoint, Pose Ambiguity, Pose Estimation.

Abstract: 3D object pose estimation by using a depth sensor is one of the important tasks in activities by robots. To reduce the pose ambiguity of an estimated object pose, several methods for multiple viewpoint pose estimation have been proposed. However, these methods need to select the viewpoints carefully to obtain better results. If the pose of the target object is ambiguous from the current observation, we could not decide where we should move the sensor to set as the next viewpoint. In this paper, we propose a best next viewpoint recommendation method by minimizing the pose ambiguity of the object by making use of the current pose estimation result as a latent variable. We evaluated viewpoints recommended by the proposed method and confirmed that it helps us to gain better pose estimation results than several comparative methods on a synthetic dataset.

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Paper citation in several formats:
Hashim, N.; Kawanishi, Y.; Deguchi, D.; Ide, I.; Murase, H.; Amma, A. and Kobori, N. (2019). Next Viewpoint Recommendation by Pose Ambiguity Minimization for Accurate Object Pose Estimation. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 60-67. DOI: 10.5220/0007366700600067

@conference{visapp19,
author={Nik Mohd Zarifie Hashim. and Yasutomo Kawanishi. and Daisuke Deguchi. and Ichiro Ide. and Hiroshi Murase. and Ayako Amma. and Norimasa Kobori.},
title={Next Viewpoint Recommendation by Pose Ambiguity Minimization for Accurate Object Pose Estimation},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={60-67},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007366700600067},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Next Viewpoint Recommendation by Pose Ambiguity Minimization for Accurate Object Pose Estimation
SN - 978-989-758-354-4
IS - 2184-4321
AU - Hashim, N.
AU - Kawanishi, Y.
AU - Deguchi, D.
AU - Ide, I.
AU - Murase, H.
AU - Amma, A.
AU - Kobori, N.
PY - 2019
SP - 60
EP - 67
DO - 10.5220/0007366700600067
PB - SciTePress