{"id":"https://openalex.org/W3200335545","doi":"https://doi.org/10.1109/mlsp52302.2021.9596204","title":"Small Moving Target MOT Tracking with GM-PHD Filter and Attention-Based CNN","display_name":"Small Moving Target MOT Tracking with GM-PHD Filter and Attention-Based CNN","publication_year":2021,"publication_date":"2021-10-25","ids":{"openalex":"https://openalex.org/W3200335545","doi":"https://doi.org/10.1109/mlsp52302.2021.9596204","mag":"3200335545"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp52302.2021.9596204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp52302.2021.9596204","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://inria.hal.science/hal-03351017","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035225081","display_name":"Camilo Aguilar","orcid":"https://orcid.org/0000-0001-9088-3377"},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en informatique et en automatique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1326498283"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Camilo Aguilar","raw_affiliation_strings":["Inria, Universit&#x00E9; C&#x00F4;te d&#x2019; Azur,Sophia Antipolis,France"],"affiliations":[{"raw_affiliation_string":"Inria, Universit&#x00E9; C&#x00F4;te d&#x2019; Azur,Sophia Antipolis,France","institution_ids":["https://openalex.org/I1326498283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018063622","display_name":"Mathias Ortner","orcid":null},"institutions":[{"id":"https://openalex.org/I112991645","display_name":"Airbus (France)","ror":"https://ror.org/023qdcg29","country_code":"FR","type":"company","lineage":["https://openalex.org/I112991645","https://openalex.org/I4210121748"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mathias Ortner","raw_affiliation_strings":["Airbus Defense and Space,Toulouse,France","Airbus Defence and Space [Toulouse] (Airbus Defence and Space SAS\r\n31 rue des Cosmonautes\r\nZ.I. du Palays\r\n31402 Toulouse Cedex 4 - France)"],"affiliations":[{"raw_affiliation_string":"Airbus Defense and Space,Toulouse,France","institution_ids":["https://openalex.org/I112991645"]},{"raw_affiliation_string":"Airbus Defence and Space [Toulouse] (Airbus Defence and Space SAS\r\n31 rue des Cosmonautes\r\nZ.I. du Palays\r\n31402 Toulouse Cedex 4 - France)","institution_ids":["https://openalex.org/I112991645"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018158883","display_name":"Josiane Zerubia","orcid":"https://orcid.org/0000-0002-7444-0856"},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en informatique et en automatique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1326498283"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Josiane Zerubia","raw_affiliation_strings":["Inria, Universit&#x00E9; C&#x00F4;te d&#x2019; Azur,Sophia Antipolis,France"],"affiliations":[{"raw_affiliation_string":"Inria, Universit&#x00E9; C&#x00F4;te d&#x2019; Azur,Sophia Antipolis,France","institution_ids":["https://openalex.org/I1326498283"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035225081"],"corresponding_institution_ids":["https://openalex.org/I1326498283"],"apc_list":null,"apc_paid":null,"fwci":0.6782,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.71673528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8122743368148804},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.7948573231697083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7642446160316467},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7131772637367249},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6168893575668335},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5647149085998535},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5349067449569702},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5017080307006836},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4980463981628418},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4721519947052002},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.45470672845840454},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.4335607886314392},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41621026396751404},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.10267651081085205}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8122743368148804},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.7948573231697083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7642446160316467},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7131772637367249},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6168893575668335},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5647149085998535},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5349067449569702},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5017080307006836},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4980463981628418},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4721519947052002},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45470672845840454},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.4335607886314392},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41621026396751404},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.10267651081085205},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mlsp52302.2021.9596204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp52302.2021.9596204","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-03351017v1","is_oa":true,"landing_page_url":"https://inria.hal.science/hal-03351017","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://2021.ieeemlsp.org/","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-03351017v1","is_oa":true,"landing_page_url":"https://inria.hal.science/hal-03351017","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://2021.ieeemlsp.org/","raw_type":"Conference papers"},"sustainable_development_goals":[{"score":0.75,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W73255329","https://openalex.org/W639708223","https://openalex.org/W1996850449","https://openalex.org/W2011425943","https://openalex.org/W2014787937","https://openalex.org/W2124781496","https://openalex.org/W2127923214","https://openalex.org/W2137585588","https://openalex.org/W2167536584","https://openalex.org/W2222512263","https://openalex.org/W2252355370","https://openalex.org/W2588370328","https://openalex.org/W2603203130","https://openalex.org/W2613718673","https://openalex.org/W2778130973","https://openalex.org/W2801120851","https://openalex.org/W2920942303","https://openalex.org/W2962896556","https://openalex.org/W2979315537","https://openalex.org/W2981393651","https://openalex.org/W2982221123","https://openalex.org/W3104218139","https://openalex.org/W3121098480","https://openalex.org/W3127131334","https://openalex.org/W3187867541"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W1981531423","https://openalex.org/W4394861761","https://openalex.org/W1977371217","https://openalex.org/W2035264131","https://openalex.org/W1679012645","https://openalex.org/W2965594636"],"abstract_inverted_index":{"We":[0,35,55,113],"present":[1,24,76],"a":[2,25,37,70,77],"multi-object":[3],"tracking":[4,130],"(MOT)":[5],"approach":[6,81],"to":[7,48,61,116],"track":[8,119],"small":[9,53],"moving":[10,121],"targets":[11],"in":[12,32],"satellite":[13],"images.":[14],"Our":[15],"objects":[16,68,122],"of":[17],"interest":[18],"span":[19],"few":[20],"pixels,":[21],"do":[22],"not":[23],"defined":[26],"texture,":[27],"and":[28,50,66,108,111,118,123],"are":[29,114],"easily":[30],"lost":[31],"cluttered":[33],"environments.":[34],"propose":[36],"patch-based":[38],"convolutional":[39],"neural":[40],"network":[41],"(CNN)":[42],"that":[43,102],"focuses":[44],"on":[45],"specific":[46],"regions":[47],"detect":[49,67,117],"discriminate":[51],"nearby":[52],"objects.":[54],"use":[56],"the":[57,63],"object":[58],"motion":[59],"information":[60],"drive":[62],"patch":[64],"selection":[65],"using":[69,83],"region-based":[71],"CNN.":[72],"In":[73],"addition,":[74],"we":[75],"direct":[78],"MOT":[79,100],"data-association":[80],"by":[82],"an":[84,96,125],"improved":[85],"Gaussian":[86],"mixture-probability":[87],"hypothesis":[88],"density":[89],"(GM-PHD)":[90],"filter.":[91],"The":[92],"GM-PHD":[93],"filter":[94],"offers":[95],"efficient":[97],"yet":[98],"robust":[99],"formulation":[101],"takes":[103],"into":[104],"account":[105],"clutter,":[106],"misdetection,":[107],"target":[109],"appearance":[110],"disappearance.":[112],"able":[115],"blob-like":[120],"demonstrate":[124],"improvement":[126],"over":[127],"competing":[128],"state-of-the-art":[129],"approaches.":[131]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
