{"id":"https://openalex.org/W2999795402","doi":"https://doi.org/10.1109/icpr48806.2021.9412999","title":"GraphBGS: Background Subtraction via Recovery of Graph Signals","display_name":"GraphBGS: Background Subtraction via Recovery of Graph Signals","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W2999795402","doi":"https://doi.org/10.1109/icpr48806.2021.9412999","mag":"2999795402"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412999","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412999","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2001.06404","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058395859","display_name":"Jhony H. Giraldo","orcid":"https://orcid.org/0000-0002-0039-1270"},"institutions":[{"id":"https://openalex.org/I78744979","display_name":"La Rochelle Universit\u00e9","ror":"https://ror.org/04mv1z119","country_code":"FR","type":"education","lineage":["https://openalex.org/I78744979"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jhony H. Giraldo","raw_affiliation_strings":["Laboratoire MIA, La Rochelle Universit\u00e9, La Rochelle, France","University of La Rochelle#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire MIA, La Rochelle Universit\u00e9, La Rochelle, France","institution_ids":["https://openalex.org/I78744979"]},{"raw_affiliation_string":"University of La Rochelle#TAB#","institution_ids":["https://openalex.org/I78744979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046143134","display_name":"Thierry Bouwmans","orcid":"https://orcid.org/0000-0003-4018-8856"},"institutions":[{"id":"https://openalex.org/I78744979","display_name":"La Rochelle Universit\u00e9","ror":"https://ror.org/04mv1z119","country_code":"FR","type":"education","lineage":["https://openalex.org/I78744979"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Thierry Bouwmans","raw_affiliation_strings":["Laboratoire MIA, La Rochelle Universit\u00e9, La Rochelle, France","University of La Rochelle#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire MIA, La Rochelle Universit\u00e9, La Rochelle, France","institution_ids":["https://openalex.org/I78744979"]},{"raw_affiliation_string":"University of La Rochelle#TAB#","institution_ids":["https://openalex.org/I78744979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78744979"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6881","last_page":"6888"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9417999982833862,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9304999709129333,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.712246835231781},{"id":"https://openalex.org/keywords/background-subtraction","display_name":"Background subtraction","score":0.6793347597122192},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6764616966247559},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6255661249160767},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6166024208068848},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5687991976737976},{"id":"https://openalex.org/keywords/subtraction","display_name":"Subtraction","score":0.5290020108222961},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47497934103012085},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.46591758728027344},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4428529739379883},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4349297881126404},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4129210412502289},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39652952551841736},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.19448760151863098},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.150811105966568},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10104021430015564},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.09476453065872192}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.712246835231781},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.6793347597122192},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6764616966247559},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6255661249160767},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6166024208068848},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5687991976737976},{"id":"https://openalex.org/C68060419","wikidata":"https://www.wikidata.org/wiki/Q40754","display_name":"Subtraction","level":2,"score":0.5290020108222961},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47497934103012085},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.46591758728027344},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4428529739379883},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4349297881126404},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4129210412502289},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39652952551841736},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.19448760151863098},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.150811105966568},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10104021430015564},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.09476453065872192},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412999","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412999","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2001.06404","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.06404","pdf_url":"https://arxiv.org/pdf/2001.06404","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2999795402","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2001.06404","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:HAL:hal-03423274v1","is_oa":true,"landing_page_url":"https://hal.science/hal-03423274","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":"2020 25th International Conference on Pattern Recognition (ICPR), Jan 2021, Milan, Italy. pp.6881-6888, &#x27E8;10.1109/ICPR48806.2021.9412999&#x27E9;","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"doi:10.48550/arxiv.2001.06404","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2001.06404","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"},{"id":"doi:10.57702/rcnjjpty","is_oa":true,"landing_page_url":"https://doi.org/10.57702/rcnjjpty","pdf_url":null,"source":{"id":"https://openalex.org/S7407053387","display_name":"TIB Data Manager","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2001.06404","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.06404","pdf_url":"https://arxiv.org/pdf/2001.06404","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":96,"referenced_works":["https://openalex.org/W607505555","https://openalex.org/W1497214886","https://openalex.org/W1578099820","https://openalex.org/W1690143098","https://openalex.org/W1861492603","https://openalex.org/W1964127768","https://openalex.org/W1970136394","https://openalex.org/W1988061476","https://openalex.org/W1990488619","https://openalex.org/W1991252559","https://openalex.org/W1994634851","https://openalex.org/W2001114276","https://openalex.org/W2005853603","https://openalex.org/W2014368295","https://openalex.org/W2024457004","https://openalex.org/W2030319053","https://openalex.org/W2052524720","https://openalex.org/W2059639989","https://openalex.org/W2062520372","https://openalex.org/W2065441822","https://openalex.org/W2067813398","https://openalex.org/W2072356364","https://openalex.org/W2073625612","https://openalex.org/W2085250279","https://openalex.org/W2091741383","https://openalex.org/W2096642693","https://openalex.org/W2101491865","https://openalex.org/W2101705628","https://openalex.org/W2102625004","https://openalex.org/W2111861511","https://openalex.org/W2118246710","https://openalex.org/W2118877769","https://openalex.org/W2121274305","https://openalex.org/W2127070222","https://openalex.org/W2156909104","https://openalex.org/W2161763921","https://openalex.org/W2163352848","https://openalex.org/W2164720308","https://openalex.org/W2168954330","https://openalex.org/W2179147795","https://openalex.org/W2195972617","https://openalex.org/W2215668387","https://openalex.org/W2339830253","https://openalex.org/W2404087539","https://openalex.org/W2475804173","https://openalex.org/W2486280681","https://openalex.org/W2525668722","https://openalex.org/W2565639579","https://openalex.org/W2606629906","https://openalex.org/W2610147486","https://openalex.org/W2620264943","https://openalex.org/W2750950678","https://openalex.org/W2751961297","https://openalex.org/W2759692151","https://openalex.org/W2783946051","https://openalex.org/W2793865950","https://openalex.org/W2796431263","https://openalex.org/W2797488090","https://openalex.org/W2886956694","https://openalex.org/W2888845200","https://openalex.org/W2901951655","https://openalex.org/W2902993091","https://openalex.org/W2910384241","https://openalex.org/W2913535645","https://openalex.org/W2949650786","https://openalex.org/W2949991997","https://openalex.org/W2950478734","https://openalex.org/W2950528699","https://openalex.org/W2952596663","https://openalex.org/W2953452037","https://openalex.org/W2959406683","https://openalex.org/W2962817598","https://openalex.org/W2962891614","https://openalex.org/W2963084556","https://openalex.org/W2963521934","https://openalex.org/W2963846024","https://openalex.org/W2964015378","https://openalex.org/W2964693622","https://openalex.org/W2983488121","https://openalex.org/W2989676862","https://openalex.org/W3016719260","https://openalex.org/W3024617482","https://openalex.org/W3034679090","https://openalex.org/W3102208898","https://openalex.org/W3105220622","https://openalex.org/W3111652977","https://openalex.org/W4229706427","https://openalex.org/W4234399496","https://openalex.org/W4236362309","https://openalex.org/W4244393449","https://openalex.org/W4300179783","https://openalex.org/W6639102338","https://openalex.org/W6674909129","https://openalex.org/W6689213722","https://openalex.org/W6722444669","https://openalex.org/W6726873649"],"related_works":["https://openalex.org/W3162834782","https://openalex.org/W3202364774","https://openalex.org/W3183705489","https://openalex.org/W2999074387","https://openalex.org/W2792020408","https://openalex.org/W2901951655","https://openalex.org/W1994634851","https://openalex.org/W2759692151","https://openalex.org/W2897606564","https://openalex.org/W3105220622","https://openalex.org/W2067813398","https://openalex.org/W3034949983","https://openalex.org/W349740100","https://openalex.org/W3088021439","https://openalex.org/W1716651123","https://openalex.org/W3119344692","https://openalex.org/W2967063638","https://openalex.org/W3179891229","https://openalex.org/W3017927394","https://openalex.org/W3000358529"],"abstract_inverted_index":{"Background":[0],"subtraction":[1,36,199],"is":[2,130],"a":[3,121,142],"fundamental":[4],"preprocessing":[5],"task":[6,11],"in":[7,14,20,40,96,113,185],"computer":[8],"vision.":[9],"This":[10],"becomes":[12],"challenging":[13,187],"real":[15],"scenarios":[16],"due":[17],"to":[18,64,93],"variations":[19],"the":[21,41,80,97,114,147,157,190],"background":[22,35,117,135,198],"for":[23,34],"both":[24],"static":[25,174],"and":[26,57,75,86,141,175,182,196],"moving":[27,176],"camera":[28,177],"sequences.":[29],"Several":[30],"deep":[31,165],"learning":[32,77,88,166],"methods":[33,167,184],"have":[37,70,89],"been":[38,71,90],"proposed":[39],"literature":[42],"with":[43],"competitive":[44,170],"performances.":[45],"However,":[46],"these":[47],"models":[48],"show":[49],"performance":[50],"degradation":[51],"when":[52],"tested":[53],"on":[54,172,189],"unseen":[55],"videos;":[56],"they":[58],"require":[59],"huge":[60],"amount":[61],"of":[62,82,99,106,108,116,149,151,159],"data":[63,163],"avoid":[65],"overfitting.":[66],"Recently,":[67],"graph-based":[68],"algorithms":[69],"successful":[72],"approaching":[73],"unsupervised":[74,181],"semi-supervised":[76,87,143],"problems.":[78],"Furthermore,":[79],"theory":[81,148],"graph":[83,109,137,139,152],"signal":[84],"processing":[85],"combined":[91],"leading":[92],"new":[94,122],"insights":[95],"field":[98],"machine":[100],"learning.":[101],"In":[102],"this":[103],"paper,":[104],"concepts":[105],"recovery":[107,150],"signals":[110],"are":[111],"introduced":[112],"problem":[115],"subtraction.":[118],"We":[119],"propose":[120],"algorithm":[123,144,155],"called":[124],"Graph":[125],"BackGround":[126],"Subtraction":[127],"(GraphBGS),":[128],"which":[129],"composed":[131],"of:":[132],"instance":[133],"segmentation,":[134],"initialization,":[136],"construction,":[138],"sampling,":[140],"inspired":[145],"from":[146],"signals.":[153],"Our":[154],"has":[156],"advantage":[158],"requiring":[160],"less":[161],"labeled":[162],"than":[164],"while":[168],"having":[169],"results":[171],"both:":[173],"videos.":[178],"GraphBGS":[179],"outperforms":[180],"supervised":[183],"several":[186],"conditions":[188],"publicly":[191],"available":[192],"Change":[193],"Detection":[194],"(CDNet2014),":[195],"UCSD":[197],"databases.":[200]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
