Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Mingyu, Hashimoto, Koichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
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
_version_ 1783322596461248512
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