{"id":"https://openalex.org/W2107775979","doi":"https://doi.org/10.1109/cvpr.2009.5206631","title":"Pedestrian detection: A benchmark","display_name":"Pedestrian detection: A benchmark","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2107775979","doi":"https://doi.org/10.1109/cvpr.2009.5206631","mag":"2107775979"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206631","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","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/A5057866698","display_name":"Piotr Doll\u00e1r","orcid":null},"institutions":[{"id":"https://openalex.org/I122411786","display_name":"California Institute of Technology","ror":"https://ror.org/05dxps055","country_code":"US","type":"education","lineage":["https://openalex.org/I122411786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Piotr Dollar","raw_affiliation_strings":["Department of Electrical Engineering, California Institute of Technology, USA","Dept of Electr. Eng., California Inst. of Technol., Pasadena, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, California Institute of Technology, USA","institution_ids":["https://openalex.org/I122411786"]},{"raw_affiliation_string":"Dept of Electr. Eng., California Inst. of Technol., Pasadena, CA, USA","institution_ids":["https://openalex.org/I122411786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026667648","display_name":"Christian Wojek","orcid":null},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian Wojek","raw_affiliation_strings":["Department of Computer Science, Technical University of Darmstadt, Germany","Dept. of Comput. Sci., Tech. Univ. Darmstadt, Darmstadt, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technical University of Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Tech. Univ. Darmstadt, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051534545","display_name":"Bernt Schiele","orcid":"https://orcid.org/0000-0001-9683-5237"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernt Schiele","raw_affiliation_strings":["Department of Computer Science, Technical University of Darmstadt, Germany","Dept. of Comput. Sci., Tech. Univ. Darmstadt, Darmstadt, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technical University of Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Tech. Univ. Darmstadt, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026825380","display_name":"Pietro Perona","orcid":"https://orcid.org/0000-0002-7583-5809"},"institutions":[{"id":"https://openalex.org/I122411786","display_name":"California Institute of Technology","ror":"https://ror.org/05dxps055","country_code":"US","type":"education","lineage":["https://openalex.org/I122411786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pietro Perona","raw_affiliation_strings":["Department of Electrical Engineering, California Institute of Technology, USA","Dept of Electr. Eng., California Inst. of Technol., Pasadena, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, California Institute of Technology, USA","institution_ids":["https://openalex.org/I122411786"]},{"raw_affiliation_string":"Dept of Electr. Eng., California Inst. of Technol., Pasadena, CA, USA","institution_ids":["https://openalex.org/I122411786"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":57.1188,"has_fulltext":false,"cited_by_count":1342,"citation_normalized_percentile":{"value":0.99945125,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"304","last_page":"311"},"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/T10036","display_name":"Advanced Neural Network Applications","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":0.9991999864578247,"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":0.8900526762008667},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.8547112941741943},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.797081470489502},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6505429148674011},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6287558078765869},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6227166056632996},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6065414547920227},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.5119372606277466},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.49750497937202454},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49512234330177307},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.42283695936203003},{"id":"https://openalex.org/keywords/advanced-driver-assistance-systems","display_name":"Advanced driver assistance systems","score":0.41813114285469055},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3213210701942444},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.26657500863075256},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.23623600602149963},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.116411954164505},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09684023261070251}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.8900526762008667},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8547112941741943},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.797081470489502},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6505429148674011},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6287558078765869},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6227166056632996},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6065414547920227},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.5119372606277466},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.49750497937202454},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49512234330177307},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42283695936203003},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.41813114285469055},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3213210701942444},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.26657500863075256},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.23623600602149963},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.116411954164505},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09684023261070251},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2009.5206631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206631","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:authors.library.caltech.edu:87172","is_oa":false,"landing_page_url":"https://resolver.caltech.edu/CaltechAUTHORS:20180615-160221639","pdf_url":null,"source":{"id":"https://openalex.org/S4306402161","display_name":"CaltechAUTHORS (California Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I122411786","host_organization_name":"California Institute of Technology","host_organization_lineage":["https://openalex.org/I122411786"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Book Section"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.212.258","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.212.258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vision.ucsd.edu/~pdollar/research/papers/CVPR09pedestrians.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W396735907","https://openalex.org/W1536943225","https://openalex.org/W1573508639","https://openalex.org/W1590105591","https://openalex.org/W1608462934","https://openalex.org/W1906375339","https://openalex.org/W1992825118","https://openalex.org/W1995444699","https://openalex.org/W2070028497","https://openalex.org/W2089181482","https://openalex.org/W2097324787","https://openalex.org/W2098699644","https://openalex.org/W2098838628","https://openalex.org/W2104679563","https://openalex.org/W2104967514","https://openalex.org/W2104974755","https://openalex.org/W2110764733","https://openalex.org/W2113201641","https://openalex.org/W2115733720","https://openalex.org/W2116022929","https://openalex.org/W2117203466","https://openalex.org/W2119823327","https://openalex.org/W2120419212","https://openalex.org/W2127499600","https://openalex.org/W2128981808","https://openalex.org/W2138302688","https://openalex.org/W2141294180","https://openalex.org/W2142645932","https://openalex.org/W2144409879","https://openalex.org/W2146352414","https://openalex.org/W2147253850","https://openalex.org/W2150298366","https://openalex.org/W2152066136","https://openalex.org/W2154740476","https://openalex.org/W2155541267","https://openalex.org/W2156539399","https://openalex.org/W2161969291","https://openalex.org/W2166623283","https://openalex.org/W2169566837","https://openalex.org/W2169671170","https://openalex.org/W2182023692","https://openalex.org/W3003662786","https://openalex.org/W3097096317","https://openalex.org/W3151111735","https://openalex.org/W4211229803","https://openalex.org/W4241222664","https://openalex.org/W6632204412","https://openalex.org/W6675929801","https://openalex.org/W6680632232","https://openalex.org/W6681508479"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2802018156","https://openalex.org/W2101531944","https://openalex.org/W4313315626","https://openalex.org/W4312696271","https://openalex.org/W4223892596","https://openalex.org/W2933098581","https://openalex.org/W2556125083","https://openalex.org/W2947029330"],"abstract_inverted_index":{"Pedestrian":[0,48],"detection":[1,108],"is":[2,51],"a":[3,68,117],"key":[4],"problem":[5],"in":[6],"computer":[7],"vision,":[8],"with":[9,71],"several":[10,106],"applications":[11],"including":[12],"robotics,":[13],"surveillance":[14],"and":[15,77,94,116],"automotive":[16],"safety.":[17],"Much":[18],"of":[19,22,33,42,54,74,113,121],"the":[20,23,31,39,46,137],"progress":[21],"past":[24],"few":[25],"years":[26],"has":[27],"been":[28],"driven":[29],"by":[30,125],"availability":[32],"challenging":[34,72],"public":[35],"datasets.":[36,59],"To":[37],"continue":[38],"rapid":[40],"rate":[41],"innovation,":[43],"we":[44,130],"introduce":[45],"Caltech":[47],"Dataset,":[49],"which":[50],"two":[52],"orders":[53],"magnitude":[55],"larger":[56],"than":[57],"existing":[58,122],"The":[60],"dataset":[61],"contains":[62],"richly":[63],"annotated":[64],"video,":[65],"recorded":[66],"from":[67],"moving":[69],"vehicle,":[70],"images":[73],"low":[75],"resolution":[76],"frequently":[78],"occluded":[79],"people.":[80],"We":[81,103],"propose":[82],"improved":[83],"evaluation":[84],"metrics,":[85],"demonstrating":[86],"that":[87],"commonly":[88],"used":[89],"per-window":[90],"measures":[91],"are":[92],"flawed":[93],"can":[95],"fail":[96],"to":[97],"predict":[98],"performance":[99,115],"on":[100],"full":[101],"images.":[102],"also":[104],"benchmark":[105],"promising":[107],"systems,":[109],"providing":[110],"an":[111],"overview":[112],"state-of-the-art":[114],"direct,":[118],"unbiased":[119],"comparison":[120],"methods.":[123],"Finally,":[124],"analyzing":[126],"common":[127],"failure":[128],"cases,":[129],"help":[131],"identify":[132],"future":[133],"research":[134],"directions":[135],"for":[136],"field.":[138]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":40},{"year":2024,"cited_by_count":68},{"year":2023,"cited_by_count":84},{"year":2022,"cited_by_count":98},{"year":2021,"cited_by_count":126},{"year":2020,"cited_by_count":120},{"year":2019,"cited_by_count":117},{"year":2018,"cited_by_count":96},{"year":2017,"cited_by_count":109},{"year":2016,"cited_by_count":65},{"year":2015,"cited_by_count":69},{"year":2014,"cited_by_count":61},{"year":2013,"cited_by_count":65},{"year":2012,"cited_by_count":61}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}