{"id":"https://openalex.org/W3160359242","doi":"https://doi.org/10.1109/aipr50011.2020.9425078","title":"Evaluation of Different Decision Fusion Mechanisms for Robust Moving Object Detection","display_name":"Evaluation of Different Decision Fusion Mechanisms for Robust Moving Object Detection","publication_year":2020,"publication_date":"2020-10-13","ids":{"openalex":"https://openalex.org/W3160359242","doi":"https://doi.org/10.1109/aipr50011.2020.9425078","mag":"3160359242"},"language":"en","primary_location":{"id":"doi:10.1109/aipr50011.2020.9425078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr50011.2020.9425078","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035597471","display_name":"Gani Rahmon","orcid":"https://orcid.org/0000-0002-4961-8229"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gani Rahmon","raw_affiliation_strings":["University of Missouri, Columbia, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Missouri, Columbia, MO, USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024182063","display_name":"Filiz Bunyak","orcid":"https://orcid.org/0000-0002-0421-6920"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Filiz Bunyak","raw_affiliation_strings":["University of Missouri, Columbia, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Missouri, Columbia, MO, USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089593576","display_name":"Guna Seetharaman","orcid":null},"institutions":[{"id":"https://openalex.org/I1288214837","display_name":"United States Naval Research Laboratory","ror":"https://ror.org/04d23a975","country_code":"US","type":"facility","lineage":["https://openalex.org/I1288214837","https://openalex.org/I1330347796","https://openalex.org/I175003984","https://openalex.org/I3130687028"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guna Seetharaman","raw_affiliation_strings":["U.S. Naval Research Laboratory, Washington, D.C"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"U.S. Naval Research Laboratory, Washington, D.C","institution_ids":["https://openalex.org/I1288214837"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025286899","display_name":"Kannappan Palaniappan","orcid":"https://orcid.org/0000-0003-2663-1380"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kannappan Palaniappan","raw_affiliation_strings":["University of Missouri, Columbia, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Missouri, Columbia, MO, USA","institution_ids":["https://openalex.org/I76835614"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9983000159263611,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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":0.8254547119140625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8067299723625183},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6674434542655945},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6092603802680969},{"id":"https://openalex.org/keywords/background-subtraction","display_name":"Background subtraction","score":0.5703357458114624},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.48601776361465454},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4253511428833008},{"id":"https://openalex.org/keywords/motion-detection","display_name":"Motion detection","score":0.41916608810424805},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.3559165596961975},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.16459420323371887},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.11284399032592773}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8254547119140625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8067299723625183},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6674434542655945},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6092603802680969},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.5703357458114624},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.48601776361465454},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4253511428833008},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.41916608810424805},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.3559165596961975},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.16459420323371887},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.11284399032592773},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr50011.2020.9425078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr50011.2020.9425078","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320316514","display_name":"Arm","ror":"https://ror.org/04mmhzs81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W285709932","https://openalex.org/W653074768","https://openalex.org/W1861492603","https://openalex.org/W1964127768","https://openalex.org/W2014324073","https://openalex.org/W2027105670","https://openalex.org/W2031489346","https://openalex.org/W2035866593","https://openalex.org/W2106167255","https://openalex.org/W2130293653","https://openalex.org/W2525668722","https://openalex.org/W2606629906","https://openalex.org/W2630837129","https://openalex.org/W2747385624","https://openalex.org/W2964098128","https://openalex.org/W4248936881","https://openalex.org/W4300179783","https://openalex.org/W6676045393","https://openalex.org/W6739696289"],"related_works":["https://openalex.org/W1987287817","https://openalex.org/W2123129869","https://openalex.org/W3094443322","https://openalex.org/W3031536623","https://openalex.org/W4399575711","https://openalex.org/W3162303681","https://openalex.org/W2182565506","https://openalex.org/W2186793300","https://openalex.org/W2100592626","https://openalex.org/W2929204938"],"abstract_inverted_index":{"A":[0],"fundamental":[1],"processing":[2,10],"step":[3],"in":[4,213],"a":[5,21,111,130,136,209],"wide":[6],"variety":[7],"of":[8,14,46,96,113,207],"video":[9],"pipelines":[11,171],"is":[12,20,143,195],"detection":[13,19,67,95,180],"moving":[15,65,97],"objects.":[16,98],"Moving":[17],"object":[18,66],"challenging":[22,163],"task":[23],"due":[24],"to":[25,76,158,197,216],"various":[26],"environmental":[27],"conditions":[28,52],"such":[29,39,53],"as":[30,40,54],"illumination":[31],"changes,":[32],"shadows,":[33],"glare,":[34],"background":[35,138],"clutter;":[36],"foreground":[37,48],"complexities":[38],"occlusion,":[41],"camouflage,":[42],"complex":[43],"motion":[44,133],"behavior":[45],"the":[47,79,177,199,217],"objects;":[49],"and":[50,87,109,118,124,135,174],"imaging":[51],"low":[55],"resolution":[56],"and/or":[57],"frame":[58],"rate,":[59],"camera":[60],"jitter":[61],"etc.":[62],"While":[63],"many":[64],"methods":[68],"have":[69],"been":[70],"proposed,":[71],"individual":[72],"approaches":[73],"often":[74],"fail":[75],"address":[77],"all":[78],"challenges":[80],"efficiently.":[81],"In":[82],"this":[83],"paper,":[84],"we":[85],"propose":[86],"evaluate":[88],"different":[89],"decision":[90,169,201],"fusion":[91,170,188,202],"mechanisms":[92],"for":[93],"robust":[94,160],"The":[99,166],"proposed":[100,167],"hybrid":[101],"system":[102],"relies":[103],"on":[104,176],"motion,":[105],"change,":[106],"appearance":[107],"cues":[108,126,155],"utilizes":[110],"mix":[112],"classical":[114],"unsupervised":[115,147],"computer":[116],"vision":[117],"supervised":[119],"deep":[120,148],"learning":[121],"approaches.":[122],"Motion":[123],"change":[125,179],"are":[127,156],"computed":[128],"through":[129],"tensor":[131],"based":[132],"estimation":[134],"multi-modal":[137],"subtraction":[139],"modules.":[140],"Appearance":[141],"cue":[142,220],"estimated":[144],"using":[145],"an":[146,205],"semantic":[149,186],"segmentation":[150],"network.":[151],"These":[152],"complementary":[153],"visual":[154],"fused":[157],"achieve":[159],"performance":[161],"under":[162],"real-world":[164],"conditions.":[165],"multi-cue":[168],"were":[172],"tested":[173],"evaluated":[175],"CDnet-2014":[178],"dataset.":[181],"Our":[182],"novel,":[183],"unsupervised,":[184],"expert-guided,":[185],"rule-based":[187],"approach":[189],"with":[190,204],"global":[191],"channel":[192],"filtering":[193],"(SR-Fusion+GCF)":[194],"shown":[196],"outperform":[198],"other":[200],"strategies":[203],"F-Measure":[206],"69%,":[208],"promising":[210],"12%":[211],"increase":[212],"F-measure":[214],"compared":[215],"best":[218],"single":[219],"approach.":[221]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
