{"id":"https://openalex.org/W2009991331","doi":"https://doi.org/10.1109/ivs.2012.6232205","title":"Moving objects detection and recognition using sparse spatial information in urban environments","display_name":"Moving objects detection and recognition using sparse spatial information in urban environments","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2009991331","doi":"https://doi.org/10.1109/ivs.2012.6232205","mag":"2009991331"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2012.6232205","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2012.6232205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Intelligent Vehicles Symposium","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/A5100401819","display_name":"You Li","orcid":"https://orcid.org/0000-0002-0152-1655"},"institutions":[{"id":"https://openalex.org/I37553959","display_name":"Universit\u00e9 de technologie de belfort-montb\u00e9liard","ror":"https://ror.org/05bn3m307","country_code":"FR","type":"education","lineage":["https://openalex.org/I37553959"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"You Li","raw_affiliation_strings":["Laboratoire Syst\u00e8mes et Transports, Universite de Technology de Belfort-Montb\u00e9liard, Belfort, France","Laboratoire Syst\u00e9mes et Transports, Universit\u00e9 de Technology de Belfort-Montb\u00e9liard, Belfort, 90010 France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire Syst\u00e8mes et Transports, Universite de Technology de Belfort-Montb\u00e9liard, Belfort, France","institution_ids":["https://openalex.org/I37553959"]},{"raw_affiliation_string":"Laboratoire Syst\u00e9mes et Transports, Universit\u00e9 de Technology de Belfort-Montb\u00e9liard, Belfort, 90010 France","institution_ids":["https://openalex.org/I37553959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083239938","display_name":"Yassine Ruichek","orcid":"https://orcid.org/0000-0003-4795-8569"},"institutions":[{"id":"https://openalex.org/I37553959","display_name":"Universit\u00e9 de technologie de belfort-montb\u00e9liard","ror":"https://ror.org/05bn3m307","country_code":"FR","type":"education","lineage":["https://openalex.org/I37553959"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Yassine Ruichek","raw_affiliation_strings":["Laboratoire Syst\u00e8mes et Transports, Universite de Technology de Belfort-Montb\u00e9liard, Belfort, France","Laboratoire Syst\u00e9mes et Transports, Universit\u00e9 de Technology de Belfort-Montb\u00e9liard, Belfort, 90010 France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire Syst\u00e8mes et Transports, Universite de Technology de Belfort-Montb\u00e9liard, Belfort, France","institution_ids":["https://openalex.org/I37553959"]},{"raw_affiliation_string":"Laboratoire Syst\u00e9mes et Transports, Universit\u00e9 de Technology de Belfort-Montb\u00e9liard, Belfort, 90010 France","institution_ids":["https://openalex.org/I37553959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37553959"],"apc_list":null,"apc_paid":null,"fwci":0.4512,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.58579769,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1060","last_page":"1065"},"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/T13282","display_name":"Automated Road and Building Extraction","score":0.996399998664856,"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"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7883934378623962},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7743343114852905},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6595717668533325},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6402396559715271},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5488725900650024},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.5340422987937927},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5105541944503784},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5089671611785889},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5036231875419617},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5025932788848877},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4802016019821167},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4472344219684601},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.41665154695510864},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.3368932902812958},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11954879760742188},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11542493104934692},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.09565389156341553}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7883934378623962},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7743343114852905},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6595717668533325},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6402396559715271},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5488725900650024},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.5340422987937927},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5105541944503784},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5089671611785889},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5036231875419617},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5025932788848877},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4802016019821167},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4472344219684601},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.41665154695510864},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.3368932902812958},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11954879760742188},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11542493104934692},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.09565389156341553},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2012.6232205","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2012.6232205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Intelligent Vehicles Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8399999737739563}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1589504938","https://openalex.org/W1608643120","https://openalex.org/W1678356000","https://openalex.org/W1913356549","https://openalex.org/W1988790447","https://openalex.org/W2011158589","https://openalex.org/W2012319351","https://openalex.org/W2021650331","https://openalex.org/W2074142320","https://openalex.org/W2076699421","https://openalex.org/W2099555712","https://openalex.org/W2109770203","https://openalex.org/W2123277060","https://openalex.org/W2124386111","https://openalex.org/W2139212933","https://openalex.org/W2140095548","https://openalex.org/W2146352414","https://openalex.org/W2153705303","https://openalex.org/W2159568070","https://openalex.org/W2161969291","https://openalex.org/W2168676389","https://openalex.org/W2911964244","https://openalex.org/W3097096317","https://openalex.org/W6635014653","https://openalex.org/W6636521847","https://openalex.org/W6639824712","https://openalex.org/W6653063046","https://openalex.org/W6675132500","https://openalex.org/W6682834485"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2914343065","https://openalex.org/W2802018156","https://openalex.org/W2963610131","https://openalex.org/W4313315626","https://openalex.org/W2101531944","https://openalex.org/W2922437833","https://openalex.org/W4312696271","https://openalex.org/W4223892596"],"abstract_inverted_index":{"Moving":[0,39],"objects":[1,40,56,95],"detection":[2,41],"and":[3,81,106],"recognition":[4],"around":[5],"an":[6,47],"intelligent":[7],"vehicle":[8],"are":[9,85,104],"active":[10],"research":[11],"fields.":[12],"A":[13],"great":[14],"number":[15],"of":[16,77,93,112,130],"approaches":[17],"have":[18],"been":[19],"proposed":[20,114],"in":[21,44,96],"recent":[22],"decades.":[23],"This":[24],"paper":[25],"proposes":[26],"a":[27,61,117,120],"novel":[28],"approach":[29],"based":[30],"solely":[31],"on":[32],"spatial":[33,66,135],"information":[34,67],"to":[35,63,88,119,126],"solve":[36],"this":[37],"problem.":[38],"is":[42,124],"achieved":[43],"conjunction":[45],"with":[46],"egomotion":[48],"estimation":[49],"by":[50,68,132],"sparse":[51],"matched":[52],"feature":[53],"points.":[54],"For":[55],"recognition,":[57],"we":[58],"firstly":[59],"present":[60],"method":[62,123],"boost":[64],"simple":[65],"Kernel":[69],"Principal":[70],"Component":[71],"Analysis":[72],"(KPCA).":[73],"Then,":[74],"two":[75],"kinds":[76],"classifiers":[78],"(Random":[79],"Forest":[80],"Gradient":[82],"Boosting":[83],"Trees)":[84],"trained":[86],"offline":[87],"recognize":[89],"several":[90],"common":[91],"categories":[92],"moving":[94],"urban":[97],"scenarios":[98],"(vehicle,":[99],"pedestrian,":[100],"cyclist,":[101],"...).":[102],"Experiments":[103],"implemented":[105],"the":[107,110,113,128,133],"results":[108],"confirm":[109],"effectiveness":[111],"algorithm.":[115],"Furthermore,":[116],"comparison":[118],"previous":[121],"similar":[122],"performed":[125],"verify":[127],"enhancement":[129],"classification":[131],"advanced":[134],"features.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}