{"id":"https://openalex.org/W2608226141","doi":"https://doi.org/10.1109/icpr.2016.7900301","title":"A late fusion approach to combine multiple pedestrian detectors","display_name":"A late fusion approach to combine multiple pedestrian detectors","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2608226141","doi":"https://doi.org/10.1109/icpr.2016.7900301","mag":"2608226141"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7900301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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/A5112859940","display_name":"Artur Jord\u00e3o","orcid":null},"institutions":[{"id":"https://openalex.org/I110200422","display_name":"Universidade Federal de Minas Gerais","ror":"https://ror.org/0176yjw32","country_code":"BR","type":"education","lineage":["https://openalex.org/I110200422"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Artur Jordao","raw_affiliation_strings":["Computer Science Department, Smart Surveillance Interest Group, Universidade Federal de Minas Gerais, Minas Gerais, Brazil"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Smart Surveillance Interest Group, Universidade Federal de Minas Gerais, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I110200422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083199464","display_name":"Jessica Sena de Souza","orcid":null},"institutions":[{"id":"https://openalex.org/I110200422","display_name":"Universidade Federal de Minas Gerais","ror":"https://ror.org/0176yjw32","country_code":"BR","type":"education","lineage":["https://openalex.org/I110200422"]},{"id":"https://openalex.org/I4210156583","display_name":"Laboratoire d'Informatique de Paris-Nord","ror":"https://ror.org/05g1zjw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I4210091279","https://openalex.org/I4210156583","https://openalex.org/I4210159245"]}],"countries":["BR","FR"],"is_corresponding":false,"raw_author_name":"Jessica Sena de Souza","raw_affiliation_strings":["Computer Science Department, Smart Surveillance Interest Group, Universidade Federal de Minas Gerais, Belo Horizonte, MG, BR"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Smart Surveillance Interest Group, Universidade Federal de Minas Gerais, Belo Horizonte, MG, BR","institution_ids":["https://openalex.org/I110200422","https://openalex.org/I4210156583"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044741265","display_name":"William Robson Schwartz","orcid":"https://orcid.org/0000-0003-1449-8834"},"institutions":[{"id":"https://openalex.org/I110200422","display_name":"Universidade Federal de Minas Gerais","ror":"https://ror.org/0176yjw32","country_code":"BR","type":"education","lineage":["https://openalex.org/I110200422"]},{"id":"https://openalex.org/I4210156583","display_name":"Laboratoire d'Informatique de Paris-Nord","ror":"https://ror.org/05g1zjw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I4210091279","https://openalex.org/I4210156583","https://openalex.org/I4210159245"]}],"countries":["BR","FR"],"is_corresponding":false,"raw_author_name":"William Robson Schwartz","raw_affiliation_strings":["Computer Science Department, Smart Surveillance Interest Group, Universidade Federal de Minas Gerais, Belo Horizonte, MG, BR"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Smart Surveillance Interest Group, Universidade Federal de Minas Gerais, Belo Horizonte, MG, BR","institution_ids":["https://openalex.org/I110200422","https://openalex.org/I4210156583"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112859940"],"corresponding_institution_ids":["https://openalex.org/I110200422"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.20220854,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"4250","last_page":"4255"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.994700014591217,"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/pedestrian-detection","display_name":"Pedestrian detection","score":0.9420978426933289},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.8844382762908936},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7751379013061523},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7280868291854858},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6229656934738159},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.592017650604248},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5895225405693054},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49416592717170715},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48181524872779846},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4593626856803894},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.4584815204143524},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4289420247077942},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37493306398391724},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34646034240722656},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.17586669325828552},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07823440432548523}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.9420978426933289},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.8844382762908936},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7751379013061523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7280868291854858},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6229656934738159},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.592017650604248},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5895225405693054},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49416592717170715},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48181524872779846},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4593626856803894},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.4584815204143524},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4289420247077942},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37493306398391724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34646034240722656},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.17586669325828552},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07823440432548523},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2016.7900301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"},{"score":0.5199999809265137,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320313934","display_name":"Institut national de recherche en informatique et en automatique (INRIA)","ror":"https://ror.org/02kvxyf05"},{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320322980","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais","ror":"https://ror.org/00nc55f03"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W173077987","https://openalex.org/W1540371141","https://openalex.org/W1650122911","https://openalex.org/W1903127635","https://openalex.org/W1951197113","https://openalex.org/W2031454541","https://openalex.org/W2034779469","https://openalex.org/W2081021369","https://openalex.org/W2087546568","https://openalex.org/W2098064689","https://openalex.org/W2107775979","https://openalex.org/W2115471590","https://openalex.org/W2136724559","https://openalex.org/W2140090057","https://openalex.org/W2151049637","https://openalex.org/W2152945944","https://openalex.org/W2159386181","https://openalex.org/W2161969291","https://openalex.org/W2169177311","https://openalex.org/W2170101770","https://openalex.org/W2265127172","https://openalex.org/W2314557688","https://openalex.org/W2324371834","https://openalex.org/W2548197316","https://openalex.org/W6632223008","https://openalex.org/W6636787326","https://openalex.org/W6639862847","https://openalex.org/W6640901054","https://openalex.org/W6674977583","https://openalex.org/W6684811926","https://openalex.org/W6684872329","https://openalex.org/W6693705612"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2608226141","https://openalex.org/W2981141433","https://openalex.org/W2802018156","https://openalex.org/W4313315626","https://openalex.org/W2101531944","https://openalex.org/W2922437833","https://openalex.org/W2100052226","https://openalex.org/W4312696271","https://openalex.org/W4223892596"],"abstract_inverted_index":{"Pedestrian":[0],"detection":[1,111],"is":[2,46,82],"a":[3,47,65],"well-known":[4],"problem":[5,49],"in":[6],"Computer":[7],"Vision.":[8],"To":[9,59],"improve":[10],"detection,":[11],"several":[12],"feature":[13],"descriptors":[14],"have":[15],"been":[16],"proposed":[17,123],"and":[18,41,57,116,136,139],"combined.":[19],"However,":[20],"there":[21],"are":[22,102],"cases":[23],"where":[24],"the":[25,37,77,86,89,94,122,132,144],"most":[26],"powerful":[27],"features":[28],"fail":[29],"to":[30,36,68,84,93,126],"discriminate":[31],"between":[32],"false":[33,90],"positives":[34,91],"similar":[35],"human":[38,78],"body":[39],"structure":[40],"actual":[42],"true":[43],"positives,":[44],"which":[45],"critical":[48],"for":[50],"applications":[51],"such":[52],"as":[53,127],"surveillance,":[54],"driving":[55],"assistance":[56],"robotics.":[58],"address":[60],"this":[61],"issue,":[62],"we":[63],"propose":[64],"novel":[66],"approach":[67],"combine":[69],"results":[70,142],"of":[71,88,96],"distinct":[72],"pedestrian":[73,110,118],"detectors":[74,101],"by":[75],"reinforcing":[76],"hypothesis.":[79],"The":[80],"method":[81],"able":[83],"reduce":[85],"confidence":[87],"due":[92],"lack":[95],"spatial":[97],"consensus":[98],"when":[99],"multiple":[100],"considered.":[103],"Our":[104],"experimental":[105],"validation,":[106],"performed":[107],"on":[108,134,143],"three":[109],"benchmarks,":[112],"INRIA":[113,135],"person,":[114],"ETH":[115,137],"Caltech":[117,145],"dataset,":[119],"demonstrates":[120],"that":[121],"approach,":[124],"referred":[125],"Spatial":[128],"Consensus":[129],"(SC),":[130],"outperforms":[131],"state-of-the-art":[133],"datasets":[138],"achieves":[140],"comparable":[141],"dataset.":[146]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}