{"id":"https://openalex.org/W2150385913","doi":"https://doi.org/10.1109/cvpr.2012.6248045","title":"Multi-pedestrian detection in crowded scenes: A global view","display_name":"Multi-pedestrian detection in crowded scenes: A global view","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2150385913","doi":"https://doi.org/10.1109/cvpr.2012.6248045","mag":"2150385913"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2012.6248045","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6248045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","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/A5054033403","display_name":"Junjie Yan","orcid":"https://orcid.org/0000-0001-8016-2277"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junjie Yan","raw_affiliation_strings":["Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109299788","display_name":"Zhen Lei","orcid":"https://orcid.org/0000-0002-0791-189X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Lei","raw_affiliation_strings":["Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063048014","display_name":"Dong Yi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Yi","raw_affiliation_strings":["Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082786719","display_name":"Stan Z. Li","orcid":"https://orcid.org/0000-0002-2961-8096"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Stan Z. Li","raw_affiliation_strings":["Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054033403"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"],"apc_list":null,"apc_paid":null,"fwci":6.3839,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.97219464,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3124","last_page":"3129"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9988999962806702,"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":0.9944000244140625,"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/pedestrian-detection","display_name":"Pedestrian detection","score":0.7619590759277344},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6939789056777954},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6770530939102173},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6732898354530334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6675816774368286},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5704224705696106},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5388744473457336},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.511648952960968},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4960385262966156},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4799923598766327},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47979456186294556},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.42694538831710815},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3896971344947815},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2196897566318512}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.7619590759277344},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6939789056777954},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6770530939102173},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6732898354530334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6675816774368286},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5704224705696106},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5388744473457336},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.511648952960968},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4960385262966156},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4799923598766327},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47979456186294556},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.42694538831710815},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3896971344947815},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2196897566318512},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","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},{"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/cvpr.2012.6248045","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6248045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.676.2794","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.676.2794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cbsr.ia.ac.cn/users/jjyan/JJYAN-CVPR2012.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1518641734","https://openalex.org/W1977470347","https://openalex.org/W1992825118","https://openalex.org/W1995444699","https://openalex.org/W1999853363","https://openalex.org/W2030536784","https://openalex.org/W2031454541","https://openalex.org/W2031489346","https://openalex.org/W2036989445","https://openalex.org/W2047221353","https://openalex.org/W2052355211","https://openalex.org/W2077513643","https://openalex.org/W2096349671","https://openalex.org/W2127420331","https://openalex.org/W2142037471","https://openalex.org/W2143516773","https://openalex.org/W2159386181","https://openalex.org/W2161841955","https://openalex.org/W2161969291","https://openalex.org/W2168356304","https://openalex.org/W2548197316","https://openalex.org/W7009134754"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W2392100589","https://openalex.org/W4205463238","https://openalex.org/W2512789322","https://openalex.org/W2972620127","https://openalex.org/W2981141433"],"abstract_inverted_index":{"Recent":[0],"state-of-the-art":[1],"algorithms":[2],"have":[3],"achieved":[4],"good":[5],"performance":[6],"on":[7,142],"normal":[8],"pedestrian":[9,13,66,80],"detection":[10,14,101],"tasks.":[11],"However,":[12],"in":[15,49,52,69],"crowded":[16,50],"scenes":[17,51],"is":[18,67,90,102],"still":[19],"challenging":[20],"due":[21],"to":[22,44,84,92,113,127],"the":[23,76,146,149],"significant":[24],"appearance":[25,55,86],"variation":[26],"caused":[27],"by":[28,75],"heavy":[29],"occlusions":[30],"and":[31,56,73,87,108,130],"complex":[32],"spatial":[33,57,95],"interactions.":[34],"In":[35],"this":[36],"paper":[37],"we":[38,109,121],"propose":[39,131],"a":[40,61,70,105,125],"unified":[41],"probabilistic":[42],"framework":[43],"globally":[45],"describe":[46],"multiple":[47],"pedestrians":[48],"terms":[53],"of":[54,79,148],"interaction.":[58,96],"We":[59],"utilize":[60,110],"mixture":[62],"model,":[63],"where":[64],"every":[65],"assumed":[68],"special":[71],"subclass":[72],"described":[74],"sub-model.":[77],"Scores":[78],"parts":[81],"are":[82],"used":[83,91],"represent":[85,93],"quadratic":[88],"kernel":[89],"relative":[94],"For":[97,117],"efficient":[98],"inference,":[99],"multi-pedestrian":[100],"modeled":[103],"as":[104,124],"MAP":[106],"problem":[107],"greedy":[111],"algorithm":[112],"get":[114],"an":[115],"approximation.":[116],"discriminative":[118],"parameter":[119],"learning,":[120],"formulate":[122],"it":[123],"learning":[126,136],"rank":[128],"problem,":[129],"Latent":[132],"Rank":[133],"SVM":[134],"for":[135],"from":[137],"weakly":[138],"labeled":[139],"data.":[140],"Experiments":[141],"various":[143],"databases":[144],"validate":[145],"effectiveness":[147],"proposed":[150],"approach.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":6}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}