Loading…
Vision-Based Pose Estimation for Textureless Space Objects by Contour Points Matching
This paper presents a novel vision-based method to solve the 6-degree-of-freedom pose estimation problem of textureless space objects from a single monocular image. Our approach follows a coarse-to-fine procedure, utilizing only shape and contour information of the input image. To achieve invariance...
Saved in:
Published in: | IEEE transactions on aerospace and electronic systems 2018-10, Vol.54 (5), p.2342-2355 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c341t-d77f8731715ab19ef0f3a9d124413c12f1c7a0a1d514b9e7ce8af15570179dba3 |
---|---|
cites | cdi_FETCH-LOGICAL-c341t-d77f8731715ab19ef0f3a9d124413c12f1c7a0a1d514b9e7ce8af15570179dba3 |
container_end_page | 2355 |
container_issue | 5 |
container_start_page | 2342 |
container_title | IEEE transactions on aerospace and electronic systems |
container_volume | 54 |
creator | Zhang, Xin Jiang, Zhiguo Zhang, Haopeng Wei, Quanmao |
description | This paper presents a novel vision-based method to solve the 6-degree-of-freedom pose estimation problem of textureless space objects from a single monocular image. Our approach follows a coarse-to-fine procedure, utilizing only shape and contour information of the input image. To achieve invariance to initialization, we select a series of projection images that are similar to the input image and establish many-to-one 2D-3D correspondences by contour feature matching. Intensive attention is focused on outlier rejection and we introduce an innovative strategy to fully utilize geometric matching information to guide pose calculation. Experiments based on simulated images are carried out, and the results manifest that pose estimation error of our approach is about 1% even in situations with heavy outlier correspondences. |
doi_str_mv | 10.1109/TAES.2018.2815879 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TAES_2018_2815879</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8315479</ieee_id><sourcerecordid>2124195201</sourcerecordid><originalsourceid>FETCH-LOGICAL-c341t-d77f8731715ab19ef0f3a9d124413c12f1c7a0a1d514b9e7ce8af15570179dba3</originalsourceid><addsrcrecordid>eNo9kE1LAzEQhoMoWKs_QLwEPG_NbDZmc6ylVaFSoa3XkM1OdEvdrUkK9t-bpcXTMDPvOx8PIbfARgBMPazG0-UoZ1CO8hJEKdUZGYAQMlOPjJ-TAUutTOUCLslVCJuUFmXBB2T90YSma7MnE7Cm711AOg2x-TYxVanrPF3hb9x73GIIdLkzFumi2qCNgVYHOuna2O19MjZtqryZaL-a9vOaXDizDXhzikOynk1Xk5dsvnh-nYznmeUFxKyW0pWSgwRhKlDomONG1ZAXBXALuQMrDTNQCygqhdJiaVz_FQOp6srwIbk_zt357mePIepNuqZNK3WepoASCUlSwVFlfReCR6d3Pn3oDxqY7unpnp7u6ekTveS5O3oaRPzXlxxEkbp_Xp1rEg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2124195201</pqid></control><display><type>article</type><title>Vision-Based Pose Estimation for Textureless Space Objects by Contour Points Matching</title><source>IEEE Electronic Library (IEL) Journals</source><creator>Zhang, Xin ; Jiang, Zhiguo ; Zhang, Haopeng ; Wei, Quanmao</creator><creatorcontrib>Zhang, Xin ; Jiang, Zhiguo ; Zhang, Haopeng ; Wei, Quanmao</creatorcontrib><description>This paper presents a novel vision-based method to solve the 6-degree-of-freedom pose estimation problem of textureless space objects from a single monocular image. Our approach follows a coarse-to-fine procedure, utilizing only shape and contour information of the input image. To achieve invariance to initialization, we select a series of projection images that are similar to the input image and establish many-to-one 2D-3D correspondences by contour feature matching. Intensive attention is focused on outlier rejection and we introduce an innovative strategy to fully utilize geometric matching information to guide pose calculation. Experiments based on simulated images are carried out, and the results manifest that pose estimation error of our approach is about 1% even in situations with heavy outlier correspondences.</description><identifier>ISSN: 0018-9251</identifier><identifier>EISSN: 1557-9603</identifier><identifier>DOI: 10.1109/TAES.2018.2815879</identifier><identifier>CODEN: IEARAX</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Cameras ; Contour feature matching ; Contour matching ; outlier rejection ; Pose estimation ; Solid modeling ; Space vehicles ; Surveillance ; textureless space object ; Three-dimensional displays ; Two dimensional displays</subject><ispartof>IEEE transactions on aerospace and electronic systems, 2018-10, Vol.54 (5), p.2342-2355</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c341t-d77f8731715ab19ef0f3a9d124413c12f1c7a0a1d514b9e7ce8af15570179dba3</citedby><cites>FETCH-LOGICAL-c341t-d77f8731715ab19ef0f3a9d124413c12f1c7a0a1d514b9e7ce8af15570179dba3</cites><orcidid>0000-0003-1981-8307 ; 0000-0001-8786-2540</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8315479$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,54794</link.rule.ids></links><search><creatorcontrib>Zhang, Xin</creatorcontrib><creatorcontrib>Jiang, Zhiguo</creatorcontrib><creatorcontrib>Zhang, Haopeng</creatorcontrib><creatorcontrib>Wei, Quanmao</creatorcontrib><title>Vision-Based Pose Estimation for Textureless Space Objects by Contour Points Matching</title><title>IEEE transactions on aerospace and electronic systems</title><addtitle>T-AES</addtitle><description>This paper presents a novel vision-based method to solve the 6-degree-of-freedom pose estimation problem of textureless space objects from a single monocular image. Our approach follows a coarse-to-fine procedure, utilizing only shape and contour information of the input image. To achieve invariance to initialization, we select a series of projection images that are similar to the input image and establish many-to-one 2D-3D correspondences by contour feature matching. Intensive attention is focused on outlier rejection and we introduce an innovative strategy to fully utilize geometric matching information to guide pose calculation. Experiments based on simulated images are carried out, and the results manifest that pose estimation error of our approach is about 1% even in situations with heavy outlier correspondences.</description><subject>Cameras</subject><subject>Contour feature matching</subject><subject>Contour matching</subject><subject>outlier rejection</subject><subject>Pose estimation</subject><subject>Solid modeling</subject><subject>Space vehicles</subject><subject>Surveillance</subject><subject>textureless space object</subject><subject>Three-dimensional displays</subject><subject>Two dimensional displays</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNo9kE1LAzEQhoMoWKs_QLwEPG_NbDZmc6ylVaFSoa3XkM1OdEvdrUkK9t-bpcXTMDPvOx8PIbfARgBMPazG0-UoZ1CO8hJEKdUZGYAQMlOPjJ-TAUutTOUCLslVCJuUFmXBB2T90YSma7MnE7Cm711AOg2x-TYxVanrPF3hb9x73GIIdLkzFumi2qCNgVYHOuna2O19MjZtqryZaL-a9vOaXDizDXhzikOynk1Xk5dsvnh-nYznmeUFxKyW0pWSgwRhKlDomONG1ZAXBXALuQMrDTNQCygqhdJiaVz_FQOp6srwIbk_zt357mePIepNuqZNK3WepoASCUlSwVFlfReCR6d3Pn3oDxqY7unpnp7u6ekTveS5O3oaRPzXlxxEkbp_Xp1rEg</recordid><startdate>20181001</startdate><enddate>20181001</enddate><creator>Zhang, Xin</creator><creator>Jiang, Zhiguo</creator><creator>Zhang, Haopeng</creator><creator>Wei, Quanmao</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-1981-8307</orcidid><orcidid>https://orcid.org/0000-0001-8786-2540</orcidid></search><sort><creationdate>20181001</creationdate><title>Vision-Based Pose Estimation for Textureless Space Objects by Contour Points Matching</title><author>Zhang, Xin ; Jiang, Zhiguo ; Zhang, Haopeng ; Wei, Quanmao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c341t-d77f8731715ab19ef0f3a9d124413c12f1c7a0a1d514b9e7ce8af15570179dba3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Cameras</topic><topic>Contour feature matching</topic><topic>Contour matching</topic><topic>outlier rejection</topic><topic>Pose estimation</topic><topic>Solid modeling</topic><topic>Space vehicles</topic><topic>Surveillance</topic><topic>textureless space object</topic><topic>Three-dimensional displays</topic><topic>Two dimensional displays</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Xin</creatorcontrib><creatorcontrib>Jiang, Zhiguo</creatorcontrib><creatorcontrib>Zhang, Haopeng</creatorcontrib><creatorcontrib>Wei, Quanmao</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on aerospace and electronic systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Xin</au><au>Jiang, Zhiguo</au><au>Zhang, Haopeng</au><au>Wei, Quanmao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Vision-Based Pose Estimation for Textureless Space Objects by Contour Points Matching</atitle><jtitle>IEEE transactions on aerospace and electronic systems</jtitle><stitle>T-AES</stitle><date>2018-10-01</date><risdate>2018</risdate><volume>54</volume><issue>5</issue><spage>2342</spage><epage>2355</epage><pages>2342-2355</pages><issn>0018-9251</issn><eissn>1557-9603</eissn><coden>IEARAX</coden><abstract>This paper presents a novel vision-based method to solve the 6-degree-of-freedom pose estimation problem of textureless space objects from a single monocular image. Our approach follows a coarse-to-fine procedure, utilizing only shape and contour information of the input image. To achieve invariance to initialization, we select a series of projection images that are similar to the input image and establish many-to-one 2D-3D correspondences by contour feature matching. Intensive attention is focused on outlier rejection and we introduce an innovative strategy to fully utilize geometric matching information to guide pose calculation. Experiments based on simulated images are carried out, and the results manifest that pose estimation error of our approach is about 1% even in situations with heavy outlier correspondences.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TAES.2018.2815879</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0003-1981-8307</orcidid><orcidid>https://orcid.org/0000-0001-8786-2540</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0018-9251 |
ispartof | IEEE transactions on aerospace and electronic systems, 2018-10, Vol.54 (5), p.2342-2355 |
issn | 0018-9251 1557-9603 |
language | eng |
recordid | cdi_crossref_primary_10_1109_TAES_2018_2815879 |
source | IEEE Electronic Library (IEL) Journals |
subjects | Cameras Contour feature matching Contour matching outlier rejection Pose estimation Solid modeling Space vehicles Surveillance textureless space object Three-dimensional displays Two dimensional displays |
title | Vision-Based Pose Estimation for Textureless Space Objects by Contour Points Matching |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T12%3A30%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Vision-Based%20Pose%20Estimation%20for%20Textureless%20Space%20Objects%20by%20Contour%20Points%20Matching&rft.jtitle=IEEE%20transactions%20on%20aerospace%20and%20electronic%20systems&rft.au=Zhang,%20Xin&rft.date=2018-10-01&rft.volume=54&rft.issue=5&rft.spage=2342&rft.epage=2355&rft.pages=2342-2355&rft.issn=0018-9251&rft.eissn=1557-9603&rft.coden=IEARAX&rft_id=info:doi/10.1109/TAES.2018.2815879&rft_dat=%3Cproquest_cross%3E2124195201%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c341t-d77f8731715ab19ef0f3a9d124413c12f1c7a0a1d514b9e7ce8af15570179dba3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2124195201&rft_id=info:pmid/&rft_ieee_id=8315479&rfr_iscdi=true |