{"id":"https://openalex.org/W2484481488","doi":"https://doi.org/10.1109/splim.2016.7528411","title":"Background subtraction for patterns of activities in cities","display_name":"Background subtraction for patterns of activities in cities","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2484481488","doi":"https://doi.org/10.1109/splim.2016.7528411","mag":"2484481488"},"language":"en","primary_location":{"id":"doi:10.1109/splim.2016.7528411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/splim.2016.7528411","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE)","raw_type":"proceedings-article"},"type":"article","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/A5024378923","display_name":"Stefanos Astaras","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162098","display_name":"Athens Information Technology","ror":"https://ror.org/05eqt7s39","country_code":"GR","type":"nonprofit","lineage":["https://openalex.org/I4210162098"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Stefanos Astaras","raw_affiliation_strings":["Athens Information Technology, Multimodal Signal Analytics, Marousi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Athens Information Technology, Multimodal Signal Analytics, Marousi","institution_ids":["https://openalex.org/I4210162098"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041821913","display_name":"Aristodemos Pnevmatikakis","orcid":"https://orcid.org/0000-0002-9623-6354"},"institutions":[{"id":"https://openalex.org/I4210162098","display_name":"Athens Information Technology","ror":"https://ror.org/05eqt7s39","country_code":"GR","type":"nonprofit","lineage":["https://openalex.org/I4210162098"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Aristodemos Pnevmatikakis","raw_affiliation_strings":["Athens Information Technology, Multimodal Signal Analytics, Marousi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Athens Information Technology, Multimodal Signal Analytics, Marousi","institution_ids":["https://openalex.org/I4210162098"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090108098","display_name":"Zheng\u2010Hua Tan","orcid":"https://orcid.org/0000-0001-6856-8928"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Zheng-Hua Tan","raw_affiliation_strings":["Department of Electronic Systems, Aalborg University, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Systems, Aalborg University, Denmark","institution_ids":["https://openalex.org/I891191580"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06133162,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"5"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9993000030517578,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9980000257492065,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/background-subtraction","display_name":"Background subtraction","score":0.9055506587028503},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7575858235359192},{"id":"https://openalex.org/keywords/crowds","display_name":"Crowds","score":0.7421778440475464},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6787065863609314},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6678302884101868},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6131128072738647},{"id":"https://openalex.org/keywords/flag","display_name":"Flag (linear algebra)","score":0.5500508546829224},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5250603556632996},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.4751160740852356},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4574728012084961},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.45326822996139526},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3474504351615906},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12285745143890381},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09907528758049011}],"concepts":[{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.9055506587028503},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7575858235359192},{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.7421778440475464},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6787065863609314},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6678302884101868},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6131128072738647},{"id":"https://openalex.org/C2776730729","wikidata":"https://www.wikidata.org/wiki/Q1392130","display_name":"Flag (linear algebra)","level":3,"score":0.5500508546829224},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5250603556632996},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.4751160740852356},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4574728012084961},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.45326822996139526},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3474504351615906},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12285745143890381},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09907528758049011},{"id":"https://openalex.org/C136119220","wikidata":"https://www.wikidata.org/wiki/Q1000660","display_name":"Algebra over a field","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/splim.2016.7528411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/splim.2016.7528411","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/0037d6f2-c327-4752-8069-54a303b26f90","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/0037d6f2-c327-4752-8069-54a303b26f90","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Astaras , S , Pnevmatikakis , A & Tan , Z-H 2016 , Background Subtraction for Patterns of Activities in Cities . in Sensing, Processing and Learning for Intelligent Machines (SPLINE), 2016 First International Workshop on . IEEE , International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE). Proceedings , The First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE2016) , Aalborg , Denmark , 06/07/2016 . https://doi.org/10.1109/SPLIM.2016.7528411","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8399999737739563,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W46659105","https://openalex.org/W1509589980","https://openalex.org/W1538962546","https://openalex.org/W1573546770","https://openalex.org/W1982853888","https://openalex.org/W2040441737","https://openalex.org/W2051111607","https://openalex.org/W2078459001","https://openalex.org/W2098305432","https://openalex.org/W2102625004","https://openalex.org/W2116076678","https://openalex.org/W2118143383","https://openalex.org/W2127070222","https://openalex.org/W2130293653","https://openalex.org/W2141572457","https://openalex.org/W2153689886","https://openalex.org/W4230354037","https://openalex.org/W4248936881","https://openalex.org/W6602002561","https://openalex.org/W6630258437","https://openalex.org/W6884942452"],"related_works":["https://openalex.org/W2324035390","https://openalex.org/W2963151310","https://openalex.org/W3175137310","https://openalex.org/W4240200267","https://openalex.org/W2583526987","https://openalex.org/W1511510665","https://openalex.org/W3034984450","https://openalex.org/W2695311495","https://openalex.org/W2154955495","https://openalex.org/W3139271019"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3,69],"learn":[4,98],"patterns":[5,101],"of":[6,19,67,74,106],"activity":[7,14,100],"in":[8,33,61,90],"open":[9],"urban":[10],"spaces":[11],"and":[12,58,102],"detect":[13,103],"outliers":[15],"that":[16,50],"represent":[17],"events":[18,105],"interest.":[20],"We":[21,83],"do":[22],"so":[23],"utilising":[24],"background":[25,76],"suppression":[26],"to":[27,55,97],"flag":[28],"people":[29],"as":[30,108],"foreground":[31],"blobs":[32],"videos":[34,92],"from":[35,52],"city":[36],"surveillance":[37],"cameras.":[38],"Since":[39],"the":[40,62,72,86,99,104],"application":[41],"domain":[42],"is":[43],"challenging,":[44],"with":[45],"far-field":[46],"cameras":[47],"viewing":[48],"scenes":[49],"vary":[51],"completely":[53],"empty":[54],"very":[56],"crowded,":[57],"each":[59],"person":[60],"crowds":[63],"being":[64],"a":[65],"handful":[66],"pixels,":[68],"first":[70],"establish":[71],"performance":[73],"different":[75],"subtraction":[77],"algorithms":[78],"using":[79],"manually":[80],"annotated":[81],"scenes.":[82],"then":[84],"apply":[85],"best-performing":[87],"SubSENSE":[88],"algorithm":[89],"off-line":[91],"collected":[93],"over":[94],"many":[95],"days,":[96],"interest":[107],"outliers.":[109]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}