{"id":"https://openalex.org/W2563578848","doi":"https://doi.org/10.1109/itsc.2016.7795979","title":"SVM based people counting method in the corridor scene using a single-layer laser scanner","display_name":"SVM based people counting method in the corridor scene using a single-layer laser scanner","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2563578848","doi":"https://doi.org/10.1109/itsc.2016.7795979","mag":"2563578848"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2016.7795979","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2016.7795979","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)","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/A5071055800","display_name":"Ziqing Chen","orcid":"https://orcid.org/0000-0001-5077-2250"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziqing Chen","raw_affiliation_strings":["Research Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081650208","display_name":"Wei Yuan","orcid":"https://orcid.org/0000-0003-4880-844X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Yuan","raw_affiliation_strings":["Department of Automation, Shanghai Key Lab of Navigation and Location Services, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Key Lab of Navigation and Location Services, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009256880","display_name":"Ming Yang","orcid":"https://orcid.org/0000-0002-8679-9137"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming Yang","raw_affiliation_strings":["Department of Automation, Shanghai Key Lab of Navigation and Location Services, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Key Lab of Navigation and Location Services, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048517656","display_name":"Chunxiang Wang","orcid":"https://orcid.org/0000-0002-6885-6740"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunxiang Wang","raw_affiliation_strings":["Research Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100382568","display_name":"Bing Wang","orcid":"https://orcid.org/0000-0003-4945-7725"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bing Wang","raw_affiliation_strings":["Department of Automation, Shanghai Key Lab of Navigation and Location Services, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Key Lab of Navigation and Location Services, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2632","last_page":"2637"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.9995999932289124,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.9707000255584717,"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/point-cloud","display_name":"Point cloud","score":0.7273523211479187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6964488625526428},{"id":"https://openalex.org/keywords/laser-scanning","display_name":"Laser scanning","score":0.6894842982292175},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.6570030450820923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6218612194061279},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6210225820541382},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6178855895996094},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.5835744142532349},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.5274860262870789},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49298974871635437},{"id":"https://openalex.org/keywords/scanner","display_name":"Scanner","score":0.4817652702331543},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.43832823634147644},{"id":"https://openalex.org/keywords/laser","display_name":"Laser","score":0.23858502507209778},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.17804089188575745},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1777293086051941},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12806543707847595},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.1242847740650177}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7273523211479187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6964488625526428},{"id":"https://openalex.org/C141349535","wikidata":"https://www.wikidata.org/wiki/Q1361664","display_name":"Laser scanning","level":3,"score":0.6894842982292175},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.6570030450820923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6218612194061279},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6210225820541382},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6178855895996094},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.5835744142532349},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5274860262870789},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49298974871635437},{"id":"https://openalex.org/C2779751349","wikidata":"https://www.wikidata.org/wiki/Q1474480","display_name":"Scanner","level":2,"score":0.4817652702331543},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.43832823634147644},{"id":"https://openalex.org/C520434653","wikidata":"https://www.wikidata.org/wiki/Q38867","display_name":"Laser","level":2,"score":0.23858502507209778},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.17804089188575745},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1777293086051941},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12806543707847595},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.1242847740650177},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2016.7795979","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2016.7795979","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6399999856948853,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1967617464","https://openalex.org/W1976749869","https://openalex.org/W2007302711","https://openalex.org/W2009805743","https://openalex.org/W2016665050","https://openalex.org/W2019469383","https://openalex.org/W2068716781","https://openalex.org/W2095653310","https://openalex.org/W2102792607","https://openalex.org/W2110686106","https://openalex.org/W2115732804","https://openalex.org/W2143946414","https://openalex.org/W2158142737","https://openalex.org/W2204366332","https://openalex.org/W2232524903","https://openalex.org/W6655141152","https://openalex.org/W6667566715"],"related_works":["https://openalex.org/W2034188527","https://openalex.org/W2195991165","https://openalex.org/W2358582870","https://openalex.org/W3005780276","https://openalex.org/W4226300986","https://openalex.org/W2129431236","https://openalex.org/W4243405716","https://openalex.org/W2060105246","https://openalex.org/W3198347806","https://openalex.org/W2179301249"],"abstract_inverted_index":{"People":[0],"counting":[1,44],"plays":[2],"an":[3],"important":[4],"role":[5],"in":[6,49,123,144],"public":[7,27],"safety,":[8],"building":[9],"automation":[10],"control":[11],"and":[12,21,93,128],"other":[13],"data":[14,92,164],"analysis":[15],"like":[16],"consumer":[17],"behaviors,":[18],"passenger":[19],"management":[20],"so":[22],"on.":[23],"Among":[24],"all":[25],"the":[26,29,34,50,56,59,66,90,97,104,112,124,139,145,153,160,169,180],"places,":[28],"corridor":[30],"is":[31,47,75,121,133,149],"one":[32],"of":[33,58,68,96,156],"most":[35],"common":[36],"scenes.":[37],"Therefore,":[38],"this":[39],"paper":[40],"proposes":[41],"a":[42,79,83,129,136,176],"people":[43],"system":[45,54],"which":[46,86,109],"applied":[48],"corridor.":[51],"The":[52,172],"proposed":[53,140,170,173],"counts":[55],"amount":[57],"passing":[60],"pedestrians":[61],"as":[62,64,135],"well":[63],"detects":[65],"direction":[67,105],"each":[69],"pedestrian.":[70,158],"A":[71,117],"mirror":[72],"reflection":[73],"device":[74],"designed":[76],"to":[77,151,167],"achieve":[78],"double-plane":[80],"scanning":[81,91,99,110],"by":[82,107],"single":[84],"lidar,":[85],"doesn't":[87],"only":[88],"double":[89],"make":[94],"use":[95],"wasted":[98],"angle,":[100],"but":[101],"also":[102],"realize":[103],"detection":[106],"judging":[108],"plane":[111],"pedestrian":[113,146,163],"has":[114],"passed":[115],"first.":[116],"novel":[118],"shape":[119],"descriptor":[120],"used":[122],"sliding":[125],"window":[126],"algorithm,":[127,141],"support":[130],"vector":[131],"machine":[132],"trained":[134],"classifier.":[137],"In":[138,159],"head-shoulder":[142],"feature":[143],"point":[147,154],"cloud":[148,155],"detected":[150],"get":[152],"every":[157],"experiment,":[161],"actual":[162],"are":[165],"collected":[166],"confirm":[168],"system.":[171],"method":[174],"shows":[175],"better":[177],"performance":[178],"than":[179],"comparison":[181],"methods.":[182]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
