{"id":"https://openalex.org/W2033186007","doi":"https://doi.org/10.1109/socpar.2011.6089113","title":"Pedestrian detection based on merged cascade classifier","display_name":"Pedestrian detection based on merged cascade classifier","publication_year":2011,"publication_date":"2011-10-01","ids":{"openalex":"https://openalex.org/W2033186007","doi":"https://doi.org/10.1109/socpar.2011.6089113","mag":"2033186007"},"language":"en","primary_location":{"id":"doi:10.1109/socpar.2011.6089113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/socpar.2011.6089113","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference of Soft Computing and Pattern Recognition (SoCPaR)","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/A5110018264","display_name":"Tian Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I7350606","display_name":"Dalian Jiaotong University","ror":"https://ror.org/05gp45n31","country_code":"CN","type":"education","lineage":["https://openalex.org/I7350606"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tian Hong","raw_affiliation_strings":["Institute of Software, Dalian Jiaotong University, Dalian, China","Institute of Software, Dalian Jiaotong University, China"],"affiliations":[{"raw_affiliation_string":"Institute of Software, Dalian Jiaotong University, Dalian, China","institution_ids":["https://openalex.org/I7350606","https://openalex.org/I4210128818"]},{"raw_affiliation_string":"Institute of Software, Dalian Jiaotong University, China","institution_ids":["https://openalex.org/I7350606","https://openalex.org/I4210128818"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101620024","display_name":"Lixia Wang","orcid":"https://orcid.org/0000-0003-0893-1259"},"institutions":[{"id":"https://openalex.org/I7350606","display_name":"Dalian Jiaotong University","ror":"https://ror.org/05gp45n31","country_code":"CN","type":"education","lineage":["https://openalex.org/I7350606"]},{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Lixia","raw_affiliation_strings":["Institute of Software, Dalian Jiaotong University, Dalian, China","Institute of Software, Dalian Jiaotong University, China"],"affiliations":[{"raw_affiliation_string":"Institute of Software, Dalian Jiaotong University, Dalian, China","institution_ids":["https://openalex.org/I7350606","https://openalex.org/I4210128818"]},{"raw_affiliation_string":"Institute of Software, Dalian Jiaotong University, China","institution_ids":["https://openalex.org/I7350606","https://openalex.org/I4210128818"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112121061","display_name":"Ding Xiaoqing","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ding Xiaoqing","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110018264"],"corresponding_institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I7350606"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.10177168,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"31","issue":null,"first_page":"237","last_page":"241"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9969000220298767,"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":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.832199215888977},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7597593069076538},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7330033779144287},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.668738067150116},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.6191564798355103},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5828164219856262},{"id":"https://openalex.org/keywords/haar-like-features","display_name":"Haar-like features","score":0.5496611595153809},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5465793013572693},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.5173284411430359},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4964020848274231},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4863641858100891},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.48537909984588623},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4635580778121948},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.4595524072647095},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.43835195899009705},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.3008127808570862},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.10802626609802246},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10409259796142578}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.832199215888977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7597593069076538},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7330033779144287},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.668738067150116},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.6191564798355103},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5828164219856262},{"id":"https://openalex.org/C123134398","wikidata":"https://www.wikidata.org/wiki/Q2493819","display_name":"Haar-like features","level":5,"score":0.5496611595153809},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5465793013572693},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.5173284411430359},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4964020848274231},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4863641858100891},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.48537909984588623},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4635580778121948},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.4595524072647095},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.43835195899009705},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.3008127808570862},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.10802626609802246},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10409259796142578},{"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/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/socpar.2011.6089113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/socpar.2011.6089113","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference of Soft Computing and Pattern Recognition (SoCPaR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6000000238418579,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1573508639","https://openalex.org/W1906375339","https://openalex.org/W1977686807","https://openalex.org/W1978491093","https://openalex.org/W1979575445","https://openalex.org/W1992825118","https://openalex.org/W2036989445","https://openalex.org/W2042322506","https://openalex.org/W2044313232","https://openalex.org/W2085254150","https://openalex.org/W2087708972","https://openalex.org/W2098999879","https://openalex.org/W2107775979","https://openalex.org/W2120815373","https://openalex.org/W2139479830","https://openalex.org/W2161969291","https://openalex.org/W2169671170","https://openalex.org/W2548197316","https://openalex.org/W2548910458","https://openalex.org/W6634262155","https://openalex.org/W6637369200","https://openalex.org/W6678246861"],"related_works":["https://openalex.org/W3135341440","https://openalex.org/W3009637957","https://openalex.org/W2431444032","https://openalex.org/W1017149716","https://openalex.org/W1970925716","https://openalex.org/W1983393909","https://openalex.org/W2585703169","https://openalex.org/W1560709653","https://openalex.org/W4318606103","https://openalex.org/W4385451546"],"abstract_inverted_index":{"Reliable":[0],"pedestrian":[1,17],"detection":[2,23,29,96,106,110],"is":[3,59],"an":[4],"important":[5],"problem":[6],"in":[7,114],"visual":[8],"surveillance.":[9],"This":[10],"paper":[11],"presents":[12],"a":[13,34],"combined":[14],"method":[15,92],"for":[16,45,61],"detection,":[18],"which":[19],"significantly":[20],"improves":[21],"the":[22,28,95,100,115],"accuracy":[24],"without":[25],"degradation":[26],"of":[27,42,105],"speed.":[30,107],"Firstly,":[31],"we":[32],"create":[33],"table":[35],"to":[36,83],"mark":[37],"foreground":[38],"pixels":[39],"by":[40],"means":[41],"background":[43,47,121],"difference":[44],"eliminating":[46],"interference":[48],"areas.":[49],"Secondly,":[50],"Weighted":[51],"Linear":[52],"Regression":[53],"Model":[54],"embedded":[55],"into":[56],"cascade":[57],"GAB":[58],"used":[60],"training":[62],"weak":[63],"classifier":[64],"with":[65,103],"parts":[66],"model":[67],"based":[68,74],"on":[69,75],"head-shoulder.":[70],"Finally,":[71],"two":[72],"classifiers":[73],"Haar-Like":[76],"features":[77,80],"and":[78,98,118],"Shapelet":[79],"respectively":[81],"fuse":[82],"detect":[84],"pedestrian.":[85],"The":[86],"experimental":[87],"results":[88],"show":[89],"that":[90],"our":[91,109],"can":[93],"boost":[94],"rate":[97],"reduce":[99],"false":[101],"alarm":[102],"non-degradation":[104],"Particularly,":[108],"mechanism":[111],"performs":[112],"well":[113],"lower":[116],"resolution":[117],"relative":[119],"complex":[120],"situation.":[122]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}