{"id":"https://openalex.org/W4402679990","doi":"https://doi.org/10.1145/3653644.3658517","title":"Real-time vehicle pedestrian detection and tracking algorithm based on computer vision","display_name":"Real-time vehicle pedestrian detection and tracking algorithm based on computer vision","publication_year":2024,"publication_date":"2024-04-26","ids":{"openalex":"https://openalex.org/W4402679990","doi":"https://doi.org/10.1145/3653644.3658517"},"language":"en","primary_location":{"id":"doi:10.1145/3653644.3658517","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3653644.3658517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd International Conference on Frontiers of Artificial Intelligence and Machine Learning","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/A5055651121","display_name":"Liping Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liping Ye","raw_affiliation_strings":["College of computer science, Wuhan Qingchuan University, Wuhan, Hubei, China, China"],"affiliations":[{"raw_affiliation_string":"College of computer science, Wuhan Qingchuan University, Wuhan, Hubei, China, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012079377","display_name":"Lang Pei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lang Pei","raw_affiliation_strings":["College of computer science, Wuhan Qingchuan University, Wuhan, Hubei,China, China"],"affiliations":[{"raw_affiliation_string":"College of computer science, Wuhan Qingchuan University, Wuhan, Hubei,China, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5055651121"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.275,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53873429,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"17","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9753999710083008,"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":0.9753999710083008,"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":0.9575999975204468,"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"}},{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9229000210762024,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.7524009943008423},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.7348013520240784},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6782936453819275},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.676516592502594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6247631311416626},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5091182589530945},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11479246616363525}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7524009943008423},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.7348013520240784},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6782936453819275},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.676516592502594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6247631311416626},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5091182589530945},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11479246616363525},{"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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3653644.3658517","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3653644.3658517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd International Conference on Frontiers of Artificial Intelligence and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2953735756","https://openalex.org/W3010592600","https://openalex.org/W3083013826","https://openalex.org/W3216523739","https://openalex.org/W4210952484","https://openalex.org/W4286284703","https://openalex.org/W4327651087","https://openalex.org/W4362631162","https://openalex.org/W4379931012"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407"],"abstract_inverted_index":{"Detection":[0],"and":[1,16,39,67,87,107,110,114,122,134,137,149,156],"tracking":[2,92,99,111,121],"of":[3,13,33,65,83,112,125,163],"vehicle":[4,148],"pedestrians":[5,68,139],"have":[6],"important":[7],"application":[8],"values":[9],"in":[10,69,129,152],"the":[11,22,25,30,41,46,52,63,73,80,84,89,98,104,120,126,130,164],"fields":[12],"intelligent":[14],"driving":[15],"traffic":[17],"monitoring.":[18],"To":[19],"this":[20],"end,":[21],"study":[23,131],"improves":[24],"YOLOv5s":[26,34,54,58],"algorithm":[27,59,93],"by":[28],"replacing":[29],"backbone":[31],"network":[32],"with":[35],"SGWin":[36],"Transformer":[37],"V2,":[38],"introduces":[40],"CBAM":[42],"module,":[43],"while":[44],"optimizing":[45],"SIoU":[47],"loss":[48],"function":[49],"to":[50,78,96,102],"obtain":[51],"improved":[53,57],"algorithm.":[55],"The":[56,116],"is":[60,76,94,132],"used":[61,77,128],"for":[62,160],"detection":[64,109,123],"vehicles":[66,113,136],"real-time":[70],"video,":[71],"then":[72],"fusion":[74],"model":[75],"correlate":[79],"motion":[81],"trajectories":[82],"detected":[85],"targets,":[86],"finally":[88],"Kalman":[90],"filter":[91],"applied":[95],"correct":[97],"prediction":[100],"results":[101,117],"realize":[103],"fast,":[105],"accurate":[106],"continuous":[108],"pedestrians.":[115],"show":[118],"that":[119],"accuracy":[124],"method":[127],"84.7%,":[133],"51":[135],"32":[138],"are":[140],"accurately":[141,146],"labeled.":[142],"Research":[143],"algorithms":[144],"can":[145],"achieve":[147],"pedestrian":[150],"recognition":[151,162],"complex":[153],"road":[154],"environments,":[155],"provide":[157],"technical":[158],"guidance":[159],"object":[161],"same":[165],"type.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}