Multitarget Detection and Tracking Method in Remote Sensing Satellite Video
A remote sensing video satellite multiple object detection and tracking method based on road masking, Gaussian mixture model (GMM), and data association is proposed. This method first extracts the road network from the remote sensing video based on deep learning. In the detection stage, the backgrou...
Gespeichert in:
| Veröffentlicht in: | Computational intelligence and neuroscience 2021, Vol.2021 (1), p.7381909-7381909 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 7381909 |
|---|---|
| container_issue | 1 |
| container_start_page | 7381909 |
| container_title | Computational intelligence and neuroscience |
| container_volume | 2021 |
| creator | Lei, Lei Guo, Dongen |
| description | A remote sensing video satellite multiple object detection and tracking method based on road masking, Gaussian mixture model (GMM), and data association is proposed. This method first extracts the road network from the remote sensing video based on deep learning. In the detection stage, the background subtraction algorithm is used based on the GMM to obtain the detection results of the moving targets on the road. In the tracking stage, the data association of the same target detection result in adjacent frames is realized based on the neighborhood search algorithm, so as to obtain the continuous tracking trajectory of each target. The experiments about multiobject detection and tracking are conducted on data measure by real remote sensing satellites, and the results verified the feasibility of the proposed method. |
| doi_str_mv | 10.1155/2021/7381909 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8426105</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A704690743</galeid><sourcerecordid>A704690743</sourcerecordid><originalsourceid>FETCH-LOGICAL-c481t-b75c6da81de3513c2282803e40b2d3435e1ece7547c9e12e5de7e802ffe4bbc33</originalsourceid><addsrcrecordid>eNp9kV1rFTEQhoMo9kPv_AEL3gj22HwneyOU-oktgq3ehmwye07qnqQmWcV_b5ZzqOhFr2aYeXiHd16EnhH8ihAhTimm5FQxTXrcP0CHRGq1ElSxh3e9FAfoqJQbjIUSmD5GB4wLQhWXh-jT5TzVUG1eQ-3eQAVXQ4qdjb67ztZ9D3HdXULdJN-F2H2BbarQXUEsy-LKVpim0Cbfgof0BD0a7VTg6b4eo6_v3l6ff1hdfH7_8fzsYuW4JnU1KOGkt5p4YIIwR6mmGjPgeKCecSaAgAMluHI9EArCgwKN6TgCHwbH2DF6vdO9nYcteAexZjuZ2xy2Nv82yQbz7yaGjVmnn0ZzKgkWTeDFXiCnHzOUarahuGbFRkhzMVQoSoluj2vo8__QmzTn2OwtFFFCSKX_Ums7gQlxTO2uW0TNmcJc9lhxdi8lNRNSYtE36mRHuZxKyTDeGSPYLImbJXGzT7zhL3f4JkRvf4X76T9NO6be</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2571755678</pqid></control><display><type>article</type><title>Multitarget Detection and Tracking Method in Remote Sensing Satellite Video</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central Open Access</source><source>Wiley Online Library Open Access</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><creator>Lei, Lei ; Guo, Dongen</creator><contributor>Ding, Bai Yuan ; Bai Yuan Ding</contributor><creatorcontrib>Lei, Lei ; Guo, Dongen ; Ding, Bai Yuan ; Bai Yuan Ding</creatorcontrib><description>A remote sensing video satellite multiple object detection and tracking method based on road masking, Gaussian mixture model (GMM), and data association is proposed. This method first extracts the road network from the remote sensing video based on deep learning. In the detection stage, the background subtraction algorithm is used based on the GMM to obtain the detection results of the moving targets on the road. In the tracking stage, the data association of the same target detection result in adjacent frames is realized based on the neighborhood search algorithm, so as to obtain the continuous tracking trajectory of each target. The experiments about multiobject detection and tracking are conducted on data measure by real remote sensing satellites, and the results verified the feasibility of the proposed method.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2021/7381909</identifier><identifier>PMID: 34512746</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Algorithms ; Cable television broadcasting industry ; Deep learning ; Information industry ; International economic relations ; Kao Tsu, Emperor of China ; Machine learning ; Methods ; Moving targets ; Multiple target tracking ; Object recognition ; Probabilistic models ; Remote sensing ; Roads ; Satellite tracking ; Satellites ; Search algorithms ; Subtraction ; Target detection ; Target recognition ; Vehicles</subject><ispartof>Computational intelligence and neuroscience, 2021, Vol.2021 (1), p.7381909-7381909</ispartof><rights>Copyright © 2021 Lei Lei and Dongen Guo.</rights><rights>COPYRIGHT 2021 John Wiley & Sons, Inc.</rights><rights>Copyright © 2021 Lei Lei and Dongen Guo. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2021 Lei Lei and Dongen Guo. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c481t-b75c6da81de3513c2282803e40b2d3435e1ece7547c9e12e5de7e802ffe4bbc33</citedby><cites>FETCH-LOGICAL-c481t-b75c6da81de3513c2282803e40b2d3435e1ece7547c9e12e5de7e802ffe4bbc33</cites><orcidid>0000-0003-3927-7616</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426105/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426105/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,728,781,785,886,4025,27924,27925,27926,53792,53794</link.rule.ids></links><search><contributor>Ding, Bai Yuan</contributor><contributor>Bai Yuan Ding</contributor><creatorcontrib>Lei, Lei</creatorcontrib><creatorcontrib>Guo, Dongen</creatorcontrib><title>Multitarget Detection and Tracking Method in Remote Sensing Satellite Video</title><title>Computational intelligence and neuroscience</title><description>A remote sensing video satellite multiple object detection and tracking method based on road masking, Gaussian mixture model (GMM), and data association is proposed. This method first extracts the road network from the remote sensing video based on deep learning. In the detection stage, the background subtraction algorithm is used based on the GMM to obtain the detection results of the moving targets on the road. In the tracking stage, the data association of the same target detection result in adjacent frames is realized based on the neighborhood search algorithm, so as to obtain the continuous tracking trajectory of each target. The experiments about multiobject detection and tracking are conducted on data measure by real remote sensing satellites, and the results verified the feasibility of the proposed method.</description><subject>Algorithms</subject><subject>Cable television broadcasting industry</subject><subject>Deep learning</subject><subject>Information industry</subject><subject>International economic relations</subject><subject>Kao Tsu, Emperor of China</subject><subject>Machine learning</subject><subject>Methods</subject><subject>Moving targets</subject><subject>Multiple target tracking</subject><subject>Object recognition</subject><subject>Probabilistic models</subject><subject>Remote sensing</subject><subject>Roads</subject><subject>Satellite tracking</subject><subject>Satellites</subject><subject>Search algorithms</subject><subject>Subtraction</subject><subject>Target detection</subject><subject>Target recognition</subject><subject>Vehicles</subject><issn>1687-5265</issn><issn>1687-5273</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kV1rFTEQhoMo9kPv_AEL3gj22HwneyOU-oktgq3ehmwye07qnqQmWcV_b5ZzqOhFr2aYeXiHd16EnhH8ihAhTimm5FQxTXrcP0CHRGq1ElSxh3e9FAfoqJQbjIUSmD5GB4wLQhWXh-jT5TzVUG1eQ-3eQAVXQ4qdjb67ztZ9D3HdXULdJN-F2H2BbarQXUEsy-LKVpim0Cbfgof0BD0a7VTg6b4eo6_v3l6ff1hdfH7_8fzsYuW4JnU1KOGkt5p4YIIwR6mmGjPgeKCecSaAgAMluHI9EArCgwKN6TgCHwbH2DF6vdO9nYcteAexZjuZ2xy2Nv82yQbz7yaGjVmnn0ZzKgkWTeDFXiCnHzOUarahuGbFRkhzMVQoSoluj2vo8__QmzTn2OwtFFFCSKX_Ums7gQlxTO2uW0TNmcJc9lhxdi8lNRNSYtE36mRHuZxKyTDeGSPYLImbJXGzT7zhL3f4JkRvf4X76T9NO6be</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Lei, Lei</creator><creator>Guo, Dongen</creator><general>Hindawi</general><general>John Wiley & Sons, Inc</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QF</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TK</scope><scope>7U5</scope><scope>7X7</scope><scope>7XB</scope><scope>8AL</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>LK8</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-3927-7616</orcidid></search><sort><creationdate>2021</creationdate><title>Multitarget Detection and Tracking Method in Remote Sensing Satellite Video</title><author>Lei, Lei ; Guo, Dongen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c481t-b75c6da81de3513c2282803e40b2d3435e1ece7547c9e12e5de7e802ffe4bbc33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Cable television broadcasting industry</topic><topic>Deep learning</topic><topic>Information industry</topic><topic>International economic relations</topic><topic>Kao Tsu, Emperor of China</topic><topic>Machine learning</topic><topic>Methods</topic><topic>Moving targets</topic><topic>Multiple target tracking</topic><topic>Object recognition</topic><topic>Probabilistic models</topic><topic>Remote sensing</topic><topic>Roads</topic><topic>Satellite tracking</topic><topic>Satellites</topic><topic>Search algorithms</topic><topic>Subtraction</topic><topic>Target detection</topic><topic>Target recognition</topic><topic>Vehicles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lei, Lei</creatorcontrib><creatorcontrib>Guo, Dongen</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aluminium Industry Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Computing Database (Alumni Edition)</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ProQuest Biological Science Collection</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Computational intelligence and neuroscience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lei, Lei</au><au>Guo, Dongen</au><au>Ding, Bai Yuan</au><au>Bai Yuan Ding</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multitarget Detection and Tracking Method in Remote Sensing Satellite Video</atitle><jtitle>Computational intelligence and neuroscience</jtitle><date>2021</date><risdate>2021</risdate><volume>2021</volume><issue>1</issue><spage>7381909</spage><epage>7381909</epage><pages>7381909-7381909</pages><issn>1687-5265</issn><eissn>1687-5273</eissn><abstract>A remote sensing video satellite multiple object detection and tracking method based on road masking, Gaussian mixture model (GMM), and data association is proposed. This method first extracts the road network from the remote sensing video based on deep learning. In the detection stage, the background subtraction algorithm is used based on the GMM to obtain the detection results of the moving targets on the road. In the tracking stage, the data association of the same target detection result in adjacent frames is realized based on the neighborhood search algorithm, so as to obtain the continuous tracking trajectory of each target. The experiments about multiobject detection and tracking are conducted on data measure by real remote sensing satellites, and the results verified the feasibility of the proposed method.</abstract><cop>New York</cop><pub>Hindawi</pub><pmid>34512746</pmid><doi>10.1155/2021/7381909</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-3927-7616</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1687-5265 |
| ispartof | Computational intelligence and neuroscience, 2021, Vol.2021 (1), p.7381909-7381909 |
| issn | 1687-5265 1687-5273 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8426105 |
| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central Open Access; Wiley Online Library Open Access; PubMed Central; Alma/SFX Local Collection |
| subjects | Algorithms Cable television broadcasting industry Deep learning Information industry International economic relations Kao Tsu, Emperor of China Machine learning Methods Moving targets Multiple target tracking Object recognition Probabilistic models Remote sensing Roads Satellite tracking Satellites Search algorithms Subtraction Target detection Target recognition Vehicles |
| title | Multitarget Detection and Tracking Method in Remote Sensing Satellite Video |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-18T13%3A56%3A17IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Multitarget%20Detection%20and%20Tracking%20Method%20in%20Remote%20Sensing%20Satellite%20Video&rft.jtitle=Computational%20intelligence%20and%20neuroscience&rft.au=Lei,%20Lei&rft.date=2021&rft.volume=2021&rft.issue=1&rft.spage=7381909&rft.epage=7381909&rft.pages=7381909-7381909&rft.issn=1687-5265&rft.eissn=1687-5273&rft_id=info:doi/10.1155/2021/7381909&rft_dat=%3Cgale_pubme%3EA704690743%3C/gale_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2571755678&rft_id=info:pmid/34512746&rft_galeid=A704690743&rfr_iscdi=true |