{"id":"https://openalex.org/W2518499265","doi":"https://doi.org/10.1109/icip.2016.7533075","title":"Automatic vehicle counting method based on principal component pursuit background modeling","display_name":"Automatic vehicle counting method based on principal component pursuit background modeling","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2518499265","doi":"https://doi.org/10.1109/icip.2016.7533075","mag":"2518499265"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7533075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7533075","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","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/A5069617607","display_name":"Jorge R. Quesada","orcid":"https://orcid.org/0000-0002-0438-0691"},"institutions":[{"id":"https://openalex.org/I65285256","display_name":"Pontificia Universidad Cat\u00f3lica del Per\u00fa","ror":"https://ror.org/00013q465","country_code":"PE","type":"education","lineage":["https://openalex.org/I65285256"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"J. Quesada","raw_affiliation_strings":["Department of Electrical Engineering, Pontificia Universidad Catolica del Peru, Lima, Peru"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Pontificia Universidad Catolica del Peru, Lima, Peru","institution_ids":["https://openalex.org/I65285256"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077092609","display_name":"Paul Rodr\u00edguez","orcid":"https://orcid.org/0000-0002-8501-0907"},"institutions":[{"id":"https://openalex.org/I65285256","display_name":"Pontificia Universidad Cat\u00f3lica del Per\u00fa","ror":"https://ror.org/00013q465","country_code":"PE","type":"education","lineage":["https://openalex.org/I65285256"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"P. Rodriguez","raw_affiliation_strings":["Department of Electrical Engineering, Pontificia Universidad Catolica del Peru, Lima, Peru"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Pontificia Universidad Catolica del Peru, Lima, Peru","institution_ids":["https://openalex.org/I65285256"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I65285256"],"apc_list":null,"apc_paid":null,"fwci":2.0129,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.94398402,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3822","last_page":"3826"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9976000189781189,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/computer-science","display_name":"Computer science","score":0.785422682762146},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.7245346307754517},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.619807779788971},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5605461001396179},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5547752976417542},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.4877103269100189},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.45422297716140747},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4526417851448059},{"id":"https://openalex.org/keywords/principal","display_name":"Principal (computer security)","score":0.42874836921691895},{"id":"https://openalex.org/keywords/foreground-detection","display_name":"Foreground detection","score":0.4187089800834656},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.41184043884277344},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.3456227481365204},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.31411319971084595},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.19672569632530212},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18699634075164795},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10703402757644653}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.785422682762146},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7245346307754517},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.619807779788971},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5605461001396179},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5547752976417542},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.4877103269100189},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.45422297716140747},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4526417851448059},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.42874836921691895},{"id":"https://openalex.org/C2779769447","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Foreground detection","level":4,"score":0.4187089800834656},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.41184043884277344},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3456227481365204},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31411319971084595},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.19672569632530212},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18699634075164795},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10703402757644653},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2016.7533075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7533075","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W41431043","https://openalex.org/W1669406372","https://openalex.org/W1971950051","https://openalex.org/W1973261441","https://openalex.org/W1981856015","https://openalex.org/W1987423623","https://openalex.org/W2025484161","https://openalex.org/W2034831901","https://openalex.org/W2041272430","https://openalex.org/W2041995828","https://openalex.org/W2045254451","https://openalex.org/W2078202596","https://openalex.org/W2091741383","https://openalex.org/W2096642693","https://openalex.org/W2099695159","https://openalex.org/W2115414933","https://openalex.org/W2118572719","https://openalex.org/W2134576786","https://openalex.org/W2145962650","https://openalex.org/W2154249783","https://openalex.org/W2158445689","https://openalex.org/W2167101305","https://openalex.org/W2233138502","https://openalex.org/W4245193022","https://openalex.org/W6661868473","https://openalex.org/W6674909129"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2036609560","https://openalex.org/W346861917","https://openalex.org/W3024018414","https://openalex.org/W2123129869","https://openalex.org/W2360918960","https://openalex.org/W1987287817"],"abstract_inverted_index":{"Estimating":[0],"the":[1,49,70,105,153,160],"number":[2,106,155],"of":[3,69,107,140,156],"vehicles":[4,108,144,157],"present":[5,109,158],"in":[6,14,110,115,133,159,167],"traffic":[7,19,112],"video":[8,52,113],"sequences":[9,114],"is":[10,45,65],"a":[11,79,98,147],"common":[12],"task":[13],"applications":[15],"such":[16,31],"as":[17,32],"active":[18],"management":[20],"and":[21,77,135,162],"automated":[22],"route":[23],"planning.":[24],"There":[25],"exist":[26],"several":[27,122],"vehicle":[28,89],"counting":[29,143],"methods":[30,76,132],"Particle":[33],"Filtering":[34],"or":[35],"Headlight":[36],"Detection,":[37],"among":[38],"others.":[39],"Although":[40],"Principal":[41],"Component":[42],"Pursuit":[43],"(PCP)":[44],"considered":[46],"to":[47,96,103,164],"be":[48],"state-of-the-art":[50,131],"for":[51,61,87],"background":[53],"modeling,":[54],"it":[55],"has":[56],"not":[57],"been":[58],"previously":[59],"exploited":[60],"this":[62,92],"task.":[63],"This":[64],"mainly":[66],"because":[67],"most":[68],"existing":[71],"PCP":[72],"algorithms":[73],"are":[74],"batch":[75],"have":[78],"high":[80],"computational":[81],"cost":[82],"that":[83,127],"makes":[84],"them":[85],"unsuitable":[86],"real-time":[88],"counting.":[90],"In":[91],"paper,":[93],"we":[94],"propose":[95],"use":[97],"novel":[99],"incremental":[100],"PCP-based":[101],"algorithm":[102],"estimate":[104],"top-view":[111],"real-time.":[116],"We":[117],"test":[118],"our":[119],"method":[120],"against":[121],"challenging":[123],"datasets,":[124],"achieving":[125],"results":[126],"compare":[128],"favorably":[129],"with":[130],"performance":[134],"speed:":[136],"an":[137],"average":[138],"accuracy":[139],"98%":[141],"when":[142,151],"passing":[145],"through":[146],"virtual":[148],"door,":[149],"91%":[150],"estimating":[152],"total":[154],"scene,":[161],"up":[163],"26":[165],"fps":[166],"processing":[168],"time.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}