{"id":"https://openalex.org/W4416688313","doi":"https://doi.org/10.1109/iccv51701.2025.01233","title":"MVTrajecter: Multi-View Pedestrian Tracking With Trajectory Motion Cost and Trajectory Appearance Cost","display_name":"MVTrajecter: Multi-View Pedestrian Tracking With Trajectory Motion Cost and Trajectory Appearance Cost","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416688313","doi":"https://doi.org/10.1109/iccv51701.2025.01233"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.01233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2509.01157","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102511251","display_name":"Taiga Yamane","orcid":null},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Taiga Yamane","raw_affiliation_strings":["NTT Corporation,NTT Human Informatics Laboratries"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation,NTT Human Informatics Laboratries","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060644399","display_name":"Ryo Masumura","orcid":"https://orcid.org/0000-0002-2415-4149"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryo Masumura","raw_affiliation_strings":["NTT Corporation,NTT Human Informatics Laboratries"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation,NTT Human Informatics Laboratries","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027868267","display_name":"Satoshi Suzuki","orcid":"https://orcid.org/0000-0001-5343-4660"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoshi Suzuki","raw_affiliation_strings":["NTT Corporation,NTT Human Informatics Laboratries"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation,NTT Human Informatics Laboratries","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013009514","display_name":"Shota Orihashi","orcid":null},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shota Orihashi","raw_affiliation_strings":["NTT Corporation,NTT Human Informatics Laboratries"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation,NTT Human Informatics Laboratries","institution_ids":["https://openalex.org/I2251713219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102511251"],"corresponding_institution_ids":["https://openalex.org/I2251713219"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34130724,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"13270","last_page":"13280"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.7384999990463257,"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":0.7384999990463257,"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":0.06430000066757202,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.05820000171661377,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/trajectory","display_name":"Trajectory","score":0.8761000037193298},{"id":"https://openalex.org/keywords/timestamp","display_name":"Timestamp","score":0.830299973487854},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6855000257492065},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6251999735832214},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5931000113487244},{"id":"https://openalex.org/keywords/tracking-system","display_name":"Tracking system","score":0.3630000054836273}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8761000037193298},{"id":"https://openalex.org/C113954288","wikidata":"https://www.wikidata.org/wiki/Q186885","display_name":"Timestamp","level":2,"score":0.830299973487854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7378000020980835},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6855000257492065},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6819999814033508},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6281999945640564},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6251999735832214},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5931000113487244},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.3630000054836273},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C95020103","wikidata":"https://www.wikidata.org/wiki/Q1813492","display_name":"Match moving","level":3,"score":0.2628999948501587},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2509.01157","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.01157","pdf_url":"https://arxiv.org/pdf/2509.01157","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2509.01157","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.01157","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2509.01157","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.01157","pdf_url":"https://arxiv.org/pdf/2509.01157","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-View":[0,80],"Pedestrian":[1],"Tracking":[2],"(MVPT)":[3],"aims":[4],"to":[5,105,156],"track":[6],"pedestrians":[7,27,43,117],"in":[8,35,90,193],"the":[9,47,57,66,119,130,154,162,176,182,188,200],"form":[10],"of":[11,42,190],"a":[12,74,137,144],"bird's":[13],"eye":[14],"view":[15],"occupancy":[16],"map":[17],"from":[18,87],"multi-view":[19],"videos.":[20],"End-to-end":[21],"methods":[22,53],"that":[23,84,158,197],"detect":[24],"and":[25,39,59,101,109,121,195],"associate":[26,157],"within":[28],"one":[29],"model":[30,155],"have":[31],"shown":[32],"great":[33],"progress":[34],"MVPT.":[36],"The":[37],"motion":[38,99,108],"appearance":[40,103,110],"information":[41,86,131],"is":[44],"important":[45],"for":[46,93],"association,":[48],"but":[49],"previous":[50,201],"end-to-end":[51,76],"MVPT":[52,77],"rely":[54],"only":[55],"on":[56,129,167],"current":[58,120,138,159],"its":[60],"single":[61],"adjacent":[62],"past":[63,67,91,123,149,164,169],"timestamp,":[64,150],"discarding":[65],"trajectories":[68,92],"before":[69],"that.":[70],"This":[71],"paper":[72],"proposes":[73],"novel":[75],"method":[78],"called":[79],"Trajectory":[81],"Tracker":[82],"(MVTrajecter)":[83],"utilizes":[85],"multiple":[88,179],"timestamps":[89,180],"robust":[94],"association.":[95],"MVTrajecter":[96,173,194],"introduces":[97],"trajectory":[98,102,165],"cost":[100,104],"effectively":[106,174],"incorporate":[107],"information,":[111],"respectively.":[112],"These":[113],"costs":[114,152],"calculate":[115],"which":[116],"at":[118,147],"each":[122,191],"timestamp":[124],"are":[125],"likely":[126],"identical":[127],"based":[128,166],"between":[132,178],"those":[133],"timestamps.":[134,170],"Even":[135],"if":[136],"pedestrian":[139,146,160],"could":[140],"be":[141],"associated":[142],"with":[143,161],"false":[145],"some":[148],"these":[151],"enable":[153],"correct":[163],"other":[168],"In":[171],"addition,":[172],"captures":[175],"relationships":[177],"leveraging":[181],"attention":[183],"mechanism.":[184],"Extensive":[185],"experiments":[186],"demonstrate":[187],"effectiveness":[189],"component":[192],"show":[196],"it":[198],"outperforms":[199],"state-of-the-art":[202],"methods.":[203]},"counts_by_year":[],"updated_date":"2026-05-06T06:03:25.996018","created_date":"2025-10-10T00:00:00"}