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Accurate Object Pose Estimation Using Depth Only
Object recognition and pose estimation is an important task in computer vision. A pose estimation algorithm using only depth information is proposed in this paper. Foreground and background points are distinguished based on their relative positions with boundaries. Model templates are selected using...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948643/ https://www.ncbi.nlm.nih.gov/pubmed/29601549 http://dx.doi.org/10.3390/s18041045 |
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author | Li, Mingyu Hashimoto, Koichi |
author_facet | Li, Mingyu Hashimoto, Koichi |
author_sort | Li, Mingyu |
collection | PubMed |
description | Object recognition and pose estimation is an important task in computer vision. A pose estimation algorithm using only depth information is proposed in this paper. Foreground and background points are distinguished based on their relative positions with boundaries. Model templates are selected using synthetic scenes to make up for the point pair feature algorithm. An accurate and fast pose verification method is introduced to select result poses from thousands of poses. Our algorithm is evaluated against a large number of scenes and proved to be more accurate than algorithms using both color information and depth information. |
format | Online Article Text |
id | pubmed-5948643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-59486432018-05-17 Accurate Object Pose Estimation Using Depth Only Li, Mingyu Hashimoto, Koichi Sensors (Basel) Article Object recognition and pose estimation is an important task in computer vision. A pose estimation algorithm using only depth information is proposed in this paper. Foreground and background points are distinguished based on their relative positions with boundaries. Model templates are selected using synthetic scenes to make up for the point pair feature algorithm. An accurate and fast pose verification method is introduced to select result poses from thousands of poses. Our algorithm is evaluated against a large number of scenes and proved to be more accurate than algorithms using both color information and depth information. MDPI 2018-03-30 /pmc/articles/PMC5948643/ /pubmed/29601549 http://dx.doi.org/10.3390/s18041045 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Mingyu Hashimoto, Koichi Accurate Object Pose Estimation Using Depth Only |
title | Accurate Object Pose Estimation Using Depth Only |
title_full | Accurate Object Pose Estimation Using Depth Only |
title_fullStr | Accurate Object Pose Estimation Using Depth Only |
title_full_unstemmed | Accurate Object Pose Estimation Using Depth Only |
title_short | Accurate Object Pose Estimation Using Depth Only |
title_sort | accurate object pose estimation using depth only |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948643/ https://www.ncbi.nlm.nih.gov/pubmed/29601549 http://dx.doi.org/10.3390/s18041045 |
work_keys_str_mv | AT limingyu accurateobjectposeestimationusingdepthonly AT hashimotokoichi accurateobjectposeestimationusingdepthonly |