{"id":"https://openalex.org/W2791837838","doi":"https://doi.org/10.1109/globalsip.2017.8308669","title":"Moving-object detection method for moving cameras by merging background subtraction and optical flow methods","display_name":"Moving-object detection method for moving cameras by merging background subtraction and optical flow methods","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2791837838","doi":"https://doi.org/10.1109/globalsip.2017.8308669","mag":"2791837838"},"language":"en","primary_location":{"id":"doi:10.1109/globalsip.2017.8308669","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2017.8308669","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","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/A5015970754","display_name":"Kengo Makino","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kengo Makino","raw_affiliation_strings":["Data Science Research Labs, NEC Corporation, Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Labs, NEC Corporation, Kanagawa, Japan","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010157078","display_name":"Takashi Shibata","orcid":"https://orcid.org/0000-0001-8072-3847"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takashi Shibata","raw_affiliation_strings":["Data Science Research Labs, NEC Corporation, Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Labs, NEC Corporation, Kanagawa, Japan","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104078314","display_name":"Shoji Yachida","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shoji Yachida","raw_affiliation_strings":["Data Science Research Labs, NEC Corporation, Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Labs, NEC Corporation, Kanagawa, Japan","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103733705","display_name":"Takuya Ogawa","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takuya Ogawa","raw_affiliation_strings":["Data Science Research Labs, NEC Corporation, Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Labs, NEC Corporation, Kanagawa, Japan","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112744684","display_name":"Katsuhiko Takahashi","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Katsuhiko Takahashi","raw_affiliation_strings":["Data Science Research Labs, NEC Corporation, Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Labs, NEC Corporation, Kanagawa, Japan","institution_ids":["https://openalex.org/I118347220"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I118347220"],"apc_list":null,"apc_paid":null,"fwci":0.4776,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.78046676,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"383","last_page":"387"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9948999881744385,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9937999844551086,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.791901707649231},{"id":"https://openalex.org/keywords/background-subtraction","display_name":"Background subtraction","score":0.7739585041999817},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7677668333053589},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7673192024230957},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.7567959427833557},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6260775327682495},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5701247453689575},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5298459529876709},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.48170334100723267},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.44827696681022644},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.31526538729667664},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17577242851257324}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.791901707649231},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.7739585041999817},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7677668333053589},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7673192024230957},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.7567959427833557},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6260775327682495},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5701247453689575},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5298459529876709},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.48170334100723267},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.44827696681022644},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31526538729667664},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17577242851257324},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globalsip.2017.8308669","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2017.8308669","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W16705709","https://openalex.org/W1521832956","https://openalex.org/W1525990217","https://openalex.org/W1578285471","https://openalex.org/W1687797484","https://openalex.org/W2025547231","https://openalex.org/W2035866593","https://openalex.org/W2059639989","https://openalex.org/W2077322237","https://openalex.org/W2090196038","https://openalex.org/W2118143383","https://openalex.org/W2118572719","https://openalex.org/W2118877769","https://openalex.org/W2127070222","https://openalex.org/W2130026429","https://openalex.org/W2142493339","https://openalex.org/W2186330282","https://openalex.org/W2294763417","https://openalex.org/W2417256080","https://openalex.org/W2536706996","https://openalex.org/W2751023760","https://openalex.org/W3040777582","https://openalex.org/W6631301939","https://openalex.org/W6677548441","https://openalex.org/W6679027886","https://openalex.org/W6780413204"],"related_works":["https://openalex.org/W2188430267","https://openalex.org/W2610698896","https://openalex.org/W2369265144","https://openalex.org/W4244119470","https://openalex.org/W1987287817","https://openalex.org/W2123129869","https://openalex.org/W3094443322","https://openalex.org/W3031536623","https://openalex.org/W4399575711","https://openalex.org/W4382050342"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,43,101],"novel":[4],"moving-object":[5],"detection":[6],"method":[7,13,189],"for":[8,33,169],"moving":[9,19,67,122,176],"cameras.":[10],"The":[11,36,62,95,116],"proposed":[12,188],"merges":[14],"two":[15,28,164],"scores":[16,166],"to":[17,77,92,136,142,154,161,167],"detect":[18,175],"objects":[20,68,177],"more":[21],"accurately":[22],"in":[23,51,79,84,144,194],"quasi-real":[24],"time.":[25],"We":[26,159],"designed":[27],"scores,":[29],"anomaly":[30,37,63],"and":[31,46,58,180],"motion,":[32],"real-time":[34],"application.":[35],"score":[38,64,97,118],"is":[39,98,105],"calculated":[40,99],"based":[41,106],"on":[42,48,107],"background":[44,60],"subtraction":[45],"depends":[47],"the":[49,55,59,66,85,93,108,121,137,150,155,191],"difference":[50],"pixel":[52,132],"intensities":[53,89,133],"between":[54],"current":[56],"image":[57],"model.":[61],"extract":[65,120],"pixels":[69,87,124],"with":[70,125,178],"high":[71,126,181],"precision":[72,147],"rate,":[73,128],"however":[74],"it":[75,140,173],"tends":[76,141],"result":[78,143],"under-detection":[80],"(low":[81,146],"recall":[82,127],"rate)":[83,148],"object":[86,151],"whose":[88],"are":[90,134],"close":[91,135],"background.":[94,138],"motion":[96,117],"from":[100],"sparse":[102,156],"optical-flow,":[103],"which":[104],"short-term":[109],"tracking":[110],"results":[111,184],"of":[112,196],"sparsely":[113],"sampled":[114],"points.":[115],"can":[119,174],"object's":[123],"even":[129],"if":[130],"those":[131],"However,":[139],"over-detection":[145],"around":[149],"boundaries":[152],"due":[153],"optical":[157],"flow.":[158],"propose":[160],"merge":[162],"these":[163],"complementary":[165],"compensate":[168],"each":[170],"other,":[171],"thus":[172],"robustness":[179],"resolution.":[182],"Experimental":[183],"showed":[185],"that":[186],"our":[187],"outperforms":[190],"conventional":[192],"methods":[193],"terms":[195],"F-measure.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
