{"id":"https://openalex.org/W2790822732","doi":"https://doi.org/10.1109/cisp-bmei.2017.8302042","title":"A passenger flow statistic algorithm based on machine learning","display_name":"A passenger flow statistic algorithm based on machine learning","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2790822732","doi":"https://doi.org/10.1109/cisp-bmei.2017.8302042","mag":"2790822732"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2017.8302042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2017.8302042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5036065528","display_name":"Xianjv Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I13175533","display_name":"Fuyang Normal University","ror":"https://ror.org/02njz9p87","country_code":"CN","type":"education","lineage":["https://openalex.org/I13175533"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xianjv Wang","raw_affiliation_strings":["School of Physics and Electronic Engineering, Fuyang Normal University, FuYang, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Electronic Engineering, Fuyang Normal University, FuYang, China","institution_ids":["https://openalex.org/I13175533"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100751112","display_name":"Shuguang Chen","orcid":"https://orcid.org/0000-0001-7366-4332"},"institutions":[{"id":"https://openalex.org/I13175533","display_name":"Fuyang Normal University","ror":"https://ror.org/02njz9p87","country_code":"CN","type":"education","lineage":["https://openalex.org/I13175533"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuguang Chen","raw_affiliation_strings":["School of Physics and Electronic Engineering, Fuyang Normal University, FuYang, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Electronic Engineering, Fuyang Normal University, FuYang, China","institution_ids":["https://openalex.org/I13175533"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067008386","display_name":"Hongjian Wei","orcid":"https://orcid.org/0000-0001-8841-5419"},"institutions":[{"id":"https://openalex.org/I13175533","display_name":"Fuyang Normal University","ror":"https://ror.org/02njz9p87","country_code":"CN","type":"education","lineage":["https://openalex.org/I13175533"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjian Wei","raw_affiliation_strings":["School of Physics and Electronic Engineering, Fuyang Normal University, FuYang, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Electronic Engineering, Fuyang Normal University, FuYang, China","institution_ids":["https://openalex.org/I13175533"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036065528"],"corresponding_institution_ids":["https://openalex.org/I13175533"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.21924647,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"30","issue":null,"first_page":"1","last_page":"5"},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9843999743461609,"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/computer-science","display_name":"Computer science","score":0.7733854055404663},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7510441541671753},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5979014039039612},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5667508840560913},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.5208583474159241},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.46553269028663635},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45965805649757385},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4436872899532318},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4409405589103699},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.425694078207016},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4222768545150757},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3752341568470001},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37342745065689087},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3466367721557617},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2182769477367401},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0970466136932373}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7733854055404663},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7510441541671753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5979014039039612},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5667508840560913},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.5208583474159241},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.46553269028663635},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45965805649757385},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4436872899532318},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4409405589103699},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.425694078207016},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4222768545150757},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3752341568470001},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37342745065689087},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3466367721557617},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2182769477367401},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0970466136932373},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2017.8302042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2017.8302042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1502057387","https://openalex.org/W2065278673","https://openalex.org/W2096343094","https://openalex.org/W2103794323","https://openalex.org/W2114701396","https://openalex.org/W2139593995","https://openalex.org/W2140235142","https://openalex.org/W2154211933","https://openalex.org/W2169282240","https://openalex.org/W2548849492","https://openalex.org/W6630080547","https://openalex.org/W6729104416"],"related_works":["https://openalex.org/W2071599417","https://openalex.org/W2048716406","https://openalex.org/W1870444468","https://openalex.org/W2979608518","https://openalex.org/W1964725559","https://openalex.org/W2767833206","https://openalex.org/W3109748140","https://openalex.org/W2045053268","https://openalex.org/W2433492094","https://openalex.org/W1556327589"],"abstract_inverted_index":{"For":[0],"the":[1,8,20,24,32,38,42,45,56,68,71,74,77,92,101,108,115,132,135,142,149,153,157,160,167],"bad":[2],"accuracy":[3,72],"and":[4,73,97,112,152],"high":[5],"costs":[6],"of":[7,23,41,50,76,159,169],"transit":[9],"passenger":[10,128],"traffic":[11],"statistics,":[12],"we":[13,164],"propose":[14],"a":[15,124],"machine":[16,102],"vision-based":[17],"algorithm.":[18,137],"As":[19],"body":[21],"parts":[22],"human":[25],"often":[26],"occur":[27],"overlap":[28],"in":[29,34,63],"congested":[30],"conditions,":[31],"algorithm":[33,85,117],"this":[35,64],"study":[36],"uses":[37,114],"overhead":[39],"image":[40],"passengers":[43,161,170],"as":[44,134],"statistic":[46],"targets.":[47],"The":[48,84],"Histogram":[49],"Oriented":[51],"Gradient":[52],"(HOG)":[53],"combined":[54],"with":[55,67],"Support":[57],"Vector":[58],"Machine":[59],"(SVM)":[60],"is":[61],"adopted":[62],"study.":[65],"Compared":[66],"traditional":[69],"methods,":[70,104],"speed":[75],"detection":[78,151],"stage":[79],"have":[80],"been":[81],"greatly":[82],"improved.":[83],"can":[86,165],"be":[87,147],"divided":[88],"into":[89],"three":[90],"steps:":[91],"target":[93,95,150,154],"detection,":[94],"tracking":[96,136],"statistics.":[98],"Based":[99],"on":[100,127],"learning":[103],"it":[105,145],"first":[106],"extracts":[107],"head":[109],"HOG":[110],"feature,":[111],"then":[113],"SVM":[116],"to":[118,122,140,162],"train":[119],"feature":[120],"sets":[121],"get":[123,166],"classifier":[125],"based":[126],"heads.":[129],"We":[130],"choose":[131],"Camshift":[133],"In":[138],"order":[139],"improve":[141],"correct":[143],"trajectory,":[144],"must":[146],"fuse":[148],"tracking.":[155],"Through":[156],"rules":[158],"alight,":[163],"number":[168],"automatically.":[171]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
