{"id":"https://openalex.org/W2508493797","doi":"https://doi.org/10.1109/tits.2016.2594816","title":"Fast and Efficient Pedestrian Detection via the Cascade Implementation of an Additive Kernel Support Vector Machine","display_name":"Fast and Efficient Pedestrian Detection via the Cascade Implementation of an Additive Kernel Support Vector Machine","publication_year":2016,"publication_date":"2016-08-25","ids":{"openalex":"https://openalex.org/W2508493797","doi":"https://doi.org/10.1109/tits.2016.2594816","mag":"2508493797"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2016.2594816","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2016.2594816","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-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/A5101870096","display_name":"Jeonghyun Baek","orcid":null},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jeonghyun Baek","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451466","display_name":"Jisu Kim","orcid":"https://orcid.org/0000-0001-7019-3475"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jisu Kim","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065415014","display_name":"Euntai Kim","orcid":"https://orcid.org/0000-0002-0975-8390"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Euntai Kim","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-0975-8390","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":4.056,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.96099728,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"18","issue":"4","first_page":"902","last_page":"916"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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":0.9079315662384033},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7696589231491089},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6866627335548401},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.6712344884872437},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.653715193271637},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6231074929237366},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.5502876043319702},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4980967044830322},{"id":"https://openalex.org/keywords/lookup-table","display_name":"Lookup table","score":0.41881391406059265},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37643933296203613},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3517243266105652},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17165091633796692},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12308800220489502}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.9079315662384033},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7696589231491089},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6866627335548401},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.6712344884872437},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.653715193271637},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6231074929237366},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5502876043319702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4980967044830322},{"id":"https://openalex.org/C134835016","wikidata":"https://www.wikidata.org/wiki/Q690265","display_name":"Lookup table","level":2,"score":0.41881391406059265},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37643933296203613},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3517243266105652},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17165091633796692},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12308800220489502},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical 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/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/tits.2016.2594816","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2016.2594816","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4456599099","display_name":null,"funder_award_id":"NRF-2016R1A2A2A05005301","funder_id":"https://openalex.org/F4320322349","funder_display_name":"Ministry of Education, Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320322349","display_name":"Ministry of Education, Science and Technology","ror":"https://ror.org/01p262204"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W99032621","https://openalex.org/W1516301787","https://openalex.org/W1564118954","https://openalex.org/W1599933961","https://openalex.org/W1906375339","https://openalex.org/W1950935069","https://openalex.org/W1981774889","https://openalex.org/W1982764079","https://openalex.org/W1984015498","https://openalex.org/W1992825118","https://openalex.org/W1999853363","https://openalex.org/W2010452185","https://openalex.org/W2031454541","https://openalex.org/W2038221881","https://openalex.org/W2041059661","https://openalex.org/W2060669513","https://openalex.org/W2077513643","https://openalex.org/W2081126192","https://openalex.org/W2087475313","https://openalex.org/W2114142878","https://openalex.org/W2119821739","https://openalex.org/W2120419212","https://openalex.org/W2121102817","https://openalex.org/W2122808326","https://openalex.org/W2125556102","https://openalex.org/W2125896931","https://openalex.org/W2134380836","https://openalex.org/W2134778014","https://openalex.org/W2135502357","https://openalex.org/W2144982973","https://openalex.org/W2146789882","https://openalex.org/W2151454023","https://openalex.org/W2155448681","https://openalex.org/W2157788863","https://openalex.org/W2159386181","https://openalex.org/W2161969291","https://openalex.org/W2165828254","https://openalex.org/W2166843422","https://openalex.org/W2168356304","https://openalex.org/W2169564179","https://openalex.org/W2179942681","https://openalex.org/W2265127172","https://openalex.org/W2534262995","https://openalex.org/W2548197316","https://openalex.org/W2976664243","https://openalex.org/W3097096317","https://openalex.org/W3151111735","https://openalex.org/W4239510810","https://openalex.org/W4285719527","https://openalex.org/W6630838125","https://openalex.org/W6635891616","https://openalex.org/W6639934059","https://openalex.org/W6640635755","https://openalex.org/W6653248712","https://openalex.org/W6660778596","https://openalex.org/W6678163432","https://openalex.org/W6680075925","https://openalex.org/W6693705612"],"related_works":["https://openalex.org/W2153719181","https://openalex.org/W1971748923","https://openalex.org/W2060986072","https://openalex.org/W1566155057","https://openalex.org/W2392100589","https://openalex.org/W2052574922","https://openalex.org/W2512789322","https://openalex.org/W2139561767","https://openalex.org/W2972620127","https://openalex.org/W2981141433"],"abstract_inverted_index":{"For":[0],"reliable":[1],"driving":[2],"assistance":[3],"or":[4],"automated":[5],"driving,":[6],"pedestrian":[7,18,51,85,105],"detection":[8,125,150],"must":[9],"be":[10,46],"robust":[11],"and":[12,95,152],"performed":[13],"in":[14,58,99],"real":[15],"time.":[16],"In":[17,68,129],"detection,":[19,52],"a":[20,30,47,56,113],"linear":[21],"support":[22],"vector":[23],"machine":[24],"(linSVM)":[25],"is":[26,79,97,110,121,127,134],"popularly":[27],"used":[28],"as":[29],"classifier":[31],"but":[32,53],"exhibits":[33],"degraded":[34],"performance":[35],"due":[36],"to":[37],"the":[38,71,75,82,118,124,131,137,145],"multipostures":[39],"of":[40,74,84],"pedestrians.":[41],"Kernel":[42],"SVM":[43],"(KSVM)":[44],"could":[45],"better":[48,149],"choice":[49],"for":[50,81],"it":[54,60,96],"has":[55,148],"disadvantage":[57],"that":[59,117,144],"requires":[61],"too":[62],"much":[63],"more":[64],"computation":[65,119,154],"than":[66],"linSVM.":[67],"this":[69],"paper,":[70],"cascade":[72,100,108],"implementation":[73,109],"additive":[76],"KSVM":[77],"(AKSVM)":[78],"proposed":[80,132,146],"application":[83],"detection.":[86,106],"AKSVM":[87],"avoids":[88],"kernel":[89],"expansion":[90],"by":[91,112],"using":[92],"lookup":[93],"tables,":[94],"implemented":[98],"form,":[101],"thereby":[102],"speeding":[103],"up":[104],"The":[107,140],"trained":[111],"genetic":[114],"algorithm":[115],"such":[116],"time":[120,155],"minimized,":[122],"whereas":[123],"accuracy":[126,151],"maximized.":[128],"experiments,":[130],"method":[133,147],"tested":[135],"with":[136,157],"INRIA":[138],"dataset.":[139],"experimental":[141],"results":[142],"indicate":[143],"reduced":[153],"compared":[156],"conventional":[158],"methods.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
