loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Shuichi Akizuki and Manabu Hashimoto

Affiliation: Chukyo University, Japan

Keyword(s): 3D Object Recognition, Hypothesis Verification, Physical Consistency, Point Cloud.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Shape Representation and Matching

Abstract: In this research, we propose a method to recognize multiple objects in the shelves of automated warehouses. The purpose of this research is to enhance the reliability of the Hypothesis Verification (HV) method that simultaneously recognizes layout of multiple objects. The proposed method have employed not only the RGB-D consistency between the input scene and the scene hypothesis but also the physical consistency. By considering the physical consistency of the scene hypothesis, the proposed HV method can efficiently reject false one. Experiment results for object which are used at Amazon Picking Challenge 2015 have been confirmed that the recognition success rate of the proposed method is higher than the previous HV method.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.226.210.133

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Akizuki, S. and Hashimoto, M. (2016). Multiple 3D Object Recognition using RGB-D Data and Physical Consistency for Automated Warehousing Robots. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP; ISBN 978-989-758-175-5; ISSN 2184-4321, SciTePress, pages 605-609. DOI: 10.5220/0005723806050609

@conference{visapp16,
author={Shuichi Akizuki. and Manabu Hashimoto.},
title={Multiple 3D Object Recognition using RGB-D Data and Physical Consistency for Automated Warehousing Robots},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP},
year={2016},
pages={605-609},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005723806050609},
isbn={978-989-758-175-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP
TI - Multiple 3D Object Recognition using RGB-D Data and Physical Consistency for Automated Warehousing Robots
SN - 978-989-758-175-5
IS - 2184-4321
AU - Akizuki, S.
AU - Hashimoto, M.
PY - 2016
SP - 605
EP - 609
DO - 10.5220/0005723806050609
PB - SciTePress