Three-dimensional trajectory estimation from image position and velocity

A recursive algorithm for estimating the three-dimensional trajectory and structure of a moving rigid object in an image sequence has been previously developed by Broida, Chandrashekhar, and Chellappa [1990]. Since then, steady advances have occurred in the calculation of optical flow. This work imp...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on aerospace and electronic systems 2000-10, Vol.36 (4), p.1075-1089
Hauptverfasser: Blostein, S.D., Zhao, L., Chann, R.M.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1089
container_issue 4
container_start_page 1075
container_title IEEE transactions on aerospace and electronic systems
container_volume 36
creator Blostein, S.D.
Zhao, L.
Chann, R.M.
description A recursive algorithm for estimating the three-dimensional trajectory and structure of a moving rigid object in an image sequence has been previously developed by Broida, Chandrashekhar, and Chellappa [1990]. Since then, steady advances have occurred in the calculation of optical flow. This work improves 3D motion trajectory and structure estimation by incorporating optical flow into the estimation framework. The new solution combines optical flow and feature point measurements and determines their statistical relationship. The feasibility of a hybrid feature point/optical flow algorithm, demonstrated through detailed simulation on synthetic and real image sequences, significantly lowers bias and mean squared error in trajectory estimation over the feature-based approach.
doi_str_mv 10.1109/7.892659
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_miscellaneous_29065779</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>892659</ieee_id><sourcerecordid>28686804</sourcerecordid><originalsourceid>FETCH-LOGICAL-c364t-4bdbef493a1839bbad7b174151b9f12e64ad4c4c4e59ba219a3889262ee9c9d83</originalsourceid><addsrcrecordid>eNqF0UFLwzAUAOAgCs4pePZUPIiXzqRNmryjDHXCwMs8h7R91Yy2mUkn7N-b2eHBy3iH8F4-Hsl7hFwzOmOMwoOcKcgKASdkwoSQKRQ0PyUTSplKIRPsnFyEsI4pVzyfkMXq0yOmte2wD9b1pk0Gb9ZYDc7vEgyD7cwQ60njXZfE5AOTjQv2t2b6OvnG1lV22F2Ss8a0Aa8O55S8Pz-t5ot0-fbyOn9cplVe8CHlZV1iwyE3TOVQlqaWJZOcCVZCwzIsuKl5FQMFlCZjYHK1_1CGCBXUKp-Su7HvxruvbXyg7myosG1Nj24bdAa0EFLCcaiKGJQfhzK2A84ivP0H127r48iCVoorJWghI7ofUeVdCB4bvfFxbH6nGdX7DWmpxw1FejNSi4h_7HD5A9vjizE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>884885067</pqid></control><display><type>article</type><title>Three-dimensional trajectory estimation from image position and velocity</title><source>IEEE Electronic Library (IEL)</source><creator>Blostein, S.D. ; Zhao, L. ; Chann, R.M.</creator><creatorcontrib>Blostein, S.D. ; Zhao, L. ; Chann, R.M.</creatorcontrib><description>A recursive algorithm for estimating the three-dimensional trajectory and structure of a moving rigid object in an image sequence has been previously developed by Broida, Chandrashekhar, and Chellappa [1990]. Since then, steady advances have occurred in the calculation of optical flow. This work improves 3D motion trajectory and structure estimation by incorporating optical flow into the estimation framework. The new solution combines optical flow and feature point measurements and determines their statistical relationship. The feasibility of a hybrid feature point/optical flow algorithm, demonstrated through detailed simulation on synthetic and real image sequences, significantly lowers bias and mean squared error in trajectory estimation over the feature-based approach.</description><identifier>ISSN: 0018-9251</identifier><identifier>EISSN: 1557-9603</identifier><identifier>DOI: 10.1109/7.892659</identifier><identifier>CODEN: IEARAX</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Estimation error ; Fluid flow measurement ; Image motion analysis ; Image sequences ; Motion estimation ; Nonlinear optics ; Optical computing ; Optical devices ; Optical filters ; Recursive estimation</subject><ispartof>IEEE transactions on aerospace and electronic systems, 2000-10, Vol.36 (4), p.1075-1089</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2000</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c364t-4bdbef493a1839bbad7b174151b9f12e64ad4c4c4e59ba219a3889262ee9c9d83</citedby><cites>FETCH-LOGICAL-c364t-4bdbef493a1839bbad7b174151b9f12e64ad4c4c4e59ba219a3889262ee9c9d83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/892659$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/892659$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Blostein, S.D.</creatorcontrib><creatorcontrib>Zhao, L.</creatorcontrib><creatorcontrib>Chann, R.M.</creatorcontrib><title>Three-dimensional trajectory estimation from image position and velocity</title><title>IEEE transactions on aerospace and electronic systems</title><addtitle>T-AES</addtitle><description>A recursive algorithm for estimating the three-dimensional trajectory and structure of a moving rigid object in an image sequence has been previously developed by Broida, Chandrashekhar, and Chellappa [1990]. Since then, steady advances have occurred in the calculation of optical flow. This work improves 3D motion trajectory and structure estimation by incorporating optical flow into the estimation framework. The new solution combines optical flow and feature point measurements and determines their statistical relationship. The feasibility of a hybrid feature point/optical flow algorithm, demonstrated through detailed simulation on synthetic and real image sequences, significantly lowers bias and mean squared error in trajectory estimation over the feature-based approach.</description><subject>Estimation error</subject><subject>Fluid flow measurement</subject><subject>Image motion analysis</subject><subject>Image sequences</subject><subject>Motion estimation</subject><subject>Nonlinear optics</subject><subject>Optical computing</subject><subject>Optical devices</subject><subject>Optical filters</subject><subject>Recursive estimation</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqF0UFLwzAUAOAgCs4pePZUPIiXzqRNmryjDHXCwMs8h7R91Yy2mUkn7N-b2eHBy3iH8F4-Hsl7hFwzOmOMwoOcKcgKASdkwoSQKRQ0PyUTSplKIRPsnFyEsI4pVzyfkMXq0yOmte2wD9b1pk0Gb9ZYDc7vEgyD7cwQ60njXZfE5AOTjQv2t2b6OvnG1lV22F2Ss8a0Aa8O55S8Pz-t5ot0-fbyOn9cplVe8CHlZV1iwyE3TOVQlqaWJZOcCVZCwzIsuKl5FQMFlCZjYHK1_1CGCBXUKp-Su7HvxruvbXyg7myosG1Nj24bdAa0EFLCcaiKGJQfhzK2A84ivP0H127r48iCVoorJWghI7ofUeVdCB4bvfFxbH6nGdX7DWmpxw1FejNSi4h_7HD5A9vjizE</recordid><startdate>200010</startdate><enddate>200010</enddate><creator>Blostein, S.D.</creator><creator>Zhao, L.</creator><creator>Chann, R.M.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><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></search><sort><creationdate>200010</creationdate><title>Three-dimensional trajectory estimation from image position and velocity</title><author>Blostein, S.D. ; Zhao, L. ; Chann, R.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-4bdbef493a1839bbad7b174151b9f12e64ad4c4c4e59ba219a3889262ee9c9d83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Estimation error</topic><topic>Fluid flow measurement</topic><topic>Image motion analysis</topic><topic>Image sequences</topic><topic>Motion estimation</topic><topic>Nonlinear optics</topic><topic>Optical computing</topic><topic>Optical devices</topic><topic>Optical filters</topic><topic>Recursive estimation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Blostein, S.D.</creatorcontrib><creatorcontrib>Zhao, L.</creatorcontrib><creatorcontrib>Chann, R.M.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Mechanical &amp; 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_linktorsrc</fulltext></delivery><addata><au>Blostein, S.D.</au><au>Zhao, L.</au><au>Chann, R.M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Three-dimensional trajectory estimation from image position and velocity</atitle><jtitle>IEEE transactions on aerospace and electronic systems</jtitle><stitle>T-AES</stitle><date>2000-10</date><risdate>2000</risdate><volume>36</volume><issue>4</issue><spage>1075</spage><epage>1089</epage><pages>1075-1089</pages><issn>0018-9251</issn><eissn>1557-9603</eissn><coden>IEARAX</coden><abstract>A recursive algorithm for estimating the three-dimensional trajectory and structure of a moving rigid object in an image sequence has been previously developed by Broida, Chandrashekhar, and Chellappa [1990]. Since then, steady advances have occurred in the calculation of optical flow. This work improves 3D motion trajectory and structure estimation by incorporating optical flow into the estimation framework. The new solution combines optical flow and feature point measurements and determines their statistical relationship. The feasibility of a hybrid feature point/optical flow algorithm, demonstrated through detailed simulation on synthetic and real image sequences, significantly lowers bias and mean squared error in trajectory estimation over the feature-based approach.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/7.892659</doi><tpages>15</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0018-9251
ispartof IEEE transactions on aerospace and electronic systems, 2000-10, Vol.36 (4), p.1075-1089
issn 0018-9251
1557-9603
language eng
recordid cdi_proquest_miscellaneous_29065779
source IEEE Electronic Library (IEL)
subjects Estimation error
Fluid flow measurement
Image motion analysis
Image sequences
Motion estimation
Nonlinear optics
Optical computing
Optical devices
Optical filters
Recursive estimation
title Three-dimensional trajectory estimation from image position and velocity
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T09%3A09%3A20IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Three-dimensional%20trajectory%20estimation%20from%20image%20position%20and%20velocity&rft.jtitle=IEEE%20transactions%20on%20aerospace%20and%20electronic%20systems&rft.au=Blostein,%20S.D.&rft.date=2000-10&rft.volume=36&rft.issue=4&rft.spage=1075&rft.epage=1089&rft.pages=1075-1089&rft.issn=0018-9251&rft.eissn=1557-9603&rft.coden=IEARAX&rft_id=info:doi/10.1109/7.892659&rft_dat=%3Cproquest_RIE%3E28686804%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=884885067&rft_id=info:pmid/&rft_ieee_id=892659&rfr_iscdi=true